diff --git a/tempscripts/injection_sandbox/analyze_c3_reasons.py b/tempscripts/injection_sandbox/analyze_c3_reasons.py
new file mode 100644
index 0000000000000000000000000000000000000000..7d15e24c126171ca5dfbc8f3018d765225b0cecf
--- /dev/null
+++ b/tempscripts/injection_sandbox/analyze_c3_reasons.py
@@ -0,0 +1,77 @@
+"""SANDBOX C3 error analysis: for each of the 51 humanized injected rows, capture
+the judge's REASONING (not just the guess), and line it up against the baseline
+reasoning for that SAME host row (from datasetreview/results/new/C3.jsonl). Lets
+us read, per example, WHY the host was caught and whether humanization addressed
+that specific tell. One judgment per row (fake in A), reasoning captured.
+
+Run from repo root:  python -u temp/injection_sandbox/analyze_c3_reasons.py
+"""
+from __future__ import annotations
+
+import json
+import logging
+import sys
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+
+import yaml
+
+for _n in ("azure", "azure.identity", "azure.core.pipeline.policies.http_logging_policy"):
+    logging.getLogger(_n).setLevel(logging.WARNING)
+
+ROOT = Path(__file__).resolve().parents[2]
+sys.path.insert(0, str(ROOT))
+from datasetreview import pipelines as P          # noqa: E402
+from datasetreview import judge_prompts as J       # noqa: E402
+from datasetreview.llm_client import make_judge     # noqa: E402
+
+SAND = Path(__file__).resolve().parent
+OUT = SAND / "out"
+MERGED = OUT / "_staging_merged_injections.jsonl"
+PROV = {p["example_id"]: p for p in json.load(open(OUT / "_merged_injections.prov.json", encoding="utf-8"))}
+BASELINE = ROOT / "datasetreview" / "results" / "new" / "C3.jsonl"
+
+cfg = yaml.safe_load(open(ROOT / "datasetreview" / "config.yaml", encoding="utf-8"))
+reals = P.real_trajectories()
+pairer = P.make_pairer(reals)
+judge = make_judge(cfg["model"])
+injected = [json.loads(l) for l in open(MERGED, encoding="utf-8") if l.strip()]
+
+base = {}
+for line in open(BASELINE, encoding="utf-8"):
+    if line.strip():
+        d = json.loads(line)
+        base[d.get("item_id")] = {"caught": d.get("caught"),
+                                  "reason": ((d.get("result") or {}).get("reasoning") or "")}
+
+
+def judge_one(fake):
+    eid = fake["example_id"]
+    real = pairer(fake)
+    msgs = J.build_c3(fake, real, swap=False)     # fake is A
+    try:
+        r = judge.judge({"system": msgs["system"], "user": msgs["user"]})
+    except Exception as e:                         # noqa: BLE001
+        return {"example_id": eid, "error": str(e)}
+    return {"example_id": eid, "host_of": PROV[eid]["host_of"], "node": PROV[eid]["rebalance_node"],
+            "confuser": PROV[eid]["confuser"], "guess": r.get("guess"),
+            "caught": r.get("guess") == "A", "confidence": r.get("confidence"),
+            "reason": r.get("reasoning") or ""}
+
+
+def main():
+    with ThreadPoolExecutor(max_workers=cfg["run"].get("workers", 4)) as ex:
+        res = list(ex.map(judge_one, injected))
+    res.sort(key=lambda r: r["example_id"])
+    for r in res:
+        r["host_baseline_caught"] = base.get(r.get("host_of"), {}).get("caught")
+        r["host_baseline_reason"] = base.get(r.get("host_of"), {}).get("reason", "")
+    (OUT / "c3_reasons.jsonl").write_text("\n".join(json.dumps(r) for r in res) + "\n", encoding="utf-8")
+    caught = sum(1 for r in res if r.get("caught"))
+    print(f"judged {len(res)} injected rows (orientation A, 1 sample). caught={caught}/{len(res)}")
+    print("wrote out/c3_reasons.jsonl")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/tempscripts/injection_sandbox/gen_merged.py b/tempscripts/injection_sandbox/gen_merged.py
new file mode 100644
index 0000000000000000000000000000000000000000..3b5cb804d0402bfe26e9b14b0c7cecea22f3eb41
--- /dev/null
+++ b/tempscripts/injection_sandbox/gen_merged.py
@@ -0,0 +1,493 @@
+"""SANDBOX generator: splice each of the 51 trie-fill injections into its
+assigned host conversation as a LATER turn (the injected row's history embeds the
+host's own prior tool turn, grounded to the host's customer). Non-destructive:
+host rows are NOT edited; we only ADD injected rows. Everything writes under
+temp/injection_sandbox/out. Reuses the proven grounded call assembly + replay
+verification from scripts/_gen_injections2.py.
+
+Run: python -u temp/injection_sandbox/gen_merged.py
+"""
+from __future__ import annotations
+
+import json
+import random
+import re
+import sys
+from collections import Counter
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[2]
+SAND = Path(__file__).resolve().parent
+sys.path.insert(0, str(ROOT))
+sys.path.insert(0, str(ROOT / "systemUpgrade" / "executor"))
+
+import scripts._gen_injections2 as G          # noqa: E402
+from fake_state import EpisodeState           # noqa: E402
+from fake_tools import TOOLS                   # noqa: E402
+
+DATA = SAND / "data"
+OUT = SAND / "out"
+OUT.mkdir(parents=True, exist_ok=True)
+
+# use the SANDBOX (clonable) free-running catalog for all grounding/replay
+CATALOG = json.load(open(DATA / "catalog.json", encoding="utf-8"))
+G.CATALOG = CATALOG
+RND = random.Random(1234)
+
+def hq_variant(leaf, on):
+    """Humanized LATER-turn query. The customer is already authenticated in the
+    host turn, so a real person would NOT restate email / name / ZIP or say
+    'look me up'. Phrase as a natural follow-up; keep the order-number literal
+    (retrieval signal); no em dashes."""
+    V = {
+        "schedule_delivery": [
+            f"Also, could you set delivery for {on} to next Tuesday?",
+            f"One more thing, can we schedule {on} to arrive on the 14th?",
+            f"While you're in there, I'd like {on} delivered next Tuesday if that works.",
+        ],
+        "request_gift_receipt": [
+            f"Oh, and could I get a gift receipt for {on}? It's a present.",
+            f"Also, {on} is a gift, so a gift receipt would be great.",
+            f"Could you include a gift receipt with {on}? It's for my sister.",
+        ],
+        "get_wishlist": [
+            "Also, can you remind me what's still on my wishlist?",
+            "While I've got you, what did I have saved on my wishlist again?",
+            "Oh, and what's left on my wishlist? I keep forgetting.",
+        ],
+        "get_order_invoice": [
+            f"Could you also send me the invoice for {on}? I need it for expenses.",
+            f"One more thing, can I get the itemized invoice for {on}?",
+            f"Also, I need the invoice for {on} for my records.",
+        ],
+        "redeem_loyalty_points": [
+            "Also, I'd like to cash in some of my loyalty points for credit.",
+            "While we're at it, can I redeem a few hundred points?",
+            "Oh, and can I put some loyalty points toward store credit?",
+        ],
+        "reorder_previous_order": [
+            f"Also, could you just reorder everything from {on}? Same as before.",
+            f"One more thing, can we duplicate order {on}? I loved that batch.",
+            f"While you're in there, could you reorder {on} for me?",
+        ],
+        "apply_gift_card": [
+            f"Also, I've got a gift card I'd like to put toward {on}.",
+            f"Oh, can we apply my gift card to {on}?",
+            f"While we're at it, please use my gift card on {on}.",
+        ],
+        "get_shipping_options": [
+            f"Also, what are the shipping options for {on}?",
+            f"One more thing, what delivery choices do I have for {on}?",
+            f"While you're there, can you tell me the shipping options on {on}?",
+        ],
+        "subscribe_to_restock_alert": [
+            f"Could you swap the out-of-stock item on {on}, and let me know when the original is back?",
+            f"Please change that item on {on}, and sign me up for a restock alert on the old one.",
+            f"Can we modify {on} to swap that item, and ping me when it restocks?",
+        ],
+        "file_shipping_insurance_claim": [
+            f"Also, {on} arrived damaged, can I file an insurance claim on it?",
+            f"One more thing, I need to file a shipping insurance claim for {on}. It came banged up.",
+        ],
+        "request_price_match": [
+            f"Also, I saw an item from {on} cheaper elsewhere, can you price match it?",
+            f"One more thing, can you price match something on {on}? Found it for less online.",
+        ],
+        "get_store_credit_balance": [
+            "Also, what's my store credit balance right now?",
+            "Oh, and how much store credit do I have left?",
+        ],
+        "set_delivery_instructions": [
+            f"Also, can you add a note to leave {on} with the doorman?",
+            f"One more thing, please have {on} left with the front desk.",
+        ],
+        "upgrade_shipping_speed": [
+            f"Also, can you bump {on} to express if it hasn't shipped yet?",
+            f"One more thing, could you upgrade {on} to overnight?",
+        ],
+    }
+    return RND.choice(V[leaf])
+
+
+CONFIRM = [
+    "All set, anything else I can help with?",
+    "Done. Let me know if you need more.",
+    "Taken care of. What else can I do?",
+    "That's handled. Anything further?",
+]
+
+
+def parse(o):
+    try:
+        return json.loads(o) if isinstance(o, str) and o.strip().startswith("{") else None
+    except json.JSONDecodeError:
+        return None
+
+
+def host_customer(host, a):
+    """Reconstruct the host's customer + order dicts, backed by the assignment."""
+    ods = {}
+    ud = None
+    for c in host["calls"]:
+        o = parse(c.get("output"))
+        if c["name"] == "get_user_details" and o and o.get("user_id"):
+            ud = o
+        if c["name"] == "get_order_details" and o and o.get("order_id"):
+            ods[o["order_id"]] = o
+    user_details = {
+        "user_id": a["uid"], "email": a["email"],
+        "name": a.get("name") or (ud or {}).get("name") or {"first_name": "Alex", "last_name": "Kim"},
+        "address": (ud or {}).get("address") or {"zip": a.get("zip", "10001")},
+        "orders": list(ods),
+    }
+    return {"uid": a["uid"], "email": a["email"], "user_details": user_details, "orders": ods}
+
+
+OPEN_LEAVES = {"schedule_delivery", "set_delivery_instructions", "get_shipping_options",
+               "upgrade_shipping_speed", "modify_pending_order_items"}
+
+
+def order_ids_for(a, u):
+    need = a["prefix"].count("get_order_details")
+    if a["node"] == "N4" and a.get("n4_orders"):
+        ids = [o for o in a["n4_orders"] if o in u["orders"]] or list(u["orders"])
+    elif a.get("grounded_order") and a["grounded_order"] in u["orders"]:
+        ids = [a["grounded_order"]] + [o for o in u["orders"] if o != a["grounded_order"]]
+    else:
+        ids = list(u["orders"])
+    # For open-required ops, ground on the most-open order the host actually has:
+    # pending/processing first, then shipped (still pre-delivery), then delivered.
+    if a["node"] != "N4" and (a["leaf"] in OPEN_LEAVES or any(t in OPEN_LEAVES for t in a["prefix"])):
+        def rank(oid):
+            st = str((u["orders"].get(oid) or {}).get("status", "")).lower()
+            if st in ("pending", "processing", "open", "pending (modified)"):
+                return 0
+            return 1 if st == "shipped" else 2
+        ids = sorted(ids, key=rank)
+    if not ids:
+        ids = ["#W0000000"]
+    while len(ids) < max(1, need):
+        ids.append(ids[0])
+    return ids
+
+
+# ---- embedded-host humanization (copy-only; canonical host rows untouched) ----
+# Targets the two dominant C3 tells in host turns while preserving EVERY DB
+# literal (order #, item id, price, quoted gift message, date, email, ZIP):
+#   T1  scripted meta preamble ("Review my recent orders, then ...")
+#   T2  trailing auth boilerplate ("... Name is X, ZIP 12345.") when that same
+#       name/ZIP/email already appears earlier in the conversation (pure dedupe)
+#   T3  assistant em/hyphen dashes ("Sure - let me ...") -> comma
+_PREAMBLE = [
+    re.compile(r"^\s*review my [\w ]{0,32}orders,\s*then\s+", re.I),
+    re.compile(r"^\s*review my [\w ]{0,32}orders and\s+", re.I),
+    re.compile(r"^\s*review my [\w ]{0,32}orders:\s*", re.I),
+    re.compile(r"^\s*look at my [\w ]{0,32}orders:\s+", re.I),
+    re.compile(r"^\s*can you look over my [\w ]{0,32}orders\?\s+", re.I),
+    re.compile(r"^\s*across (?:my )?[\w ]{0,32}orders:\s+", re.I),
+]
+_TRAIL_NAMEZIP = re.compile(
+    r"\s*(?:my name is|name is)\s+([A-Za-z]+(?:\s+[A-Za-z]+)?),?\s*"
+    r"(?:and\s+(?:my\s+)?)?zip(?:\s+is|\s+code\s+is|:)?\s*(\d{5})\.?\s*$", re.I)
+_TRAIL_EMAIL = re.compile(r"\s*my email is\s+([^\s,]+@[^\s,]+?)\.?\s*$", re.I)
+
+
+def _cap(s):
+    return s[:1].upper() + s[1:] if s else s
+
+
+def humanize_host_query(q, history_text):
+    for pat in _PREAMBLE:
+        m = pat.match(q)
+        if m:
+            q = _cap(q[m.end():].lstrip())
+            break
+    m = _TRAIL_NAMEZIP.search(q)
+    if m and (m.group(1) in history_text and m.group(2) in history_text):
+        q = q[:m.start()].rstrip()
+        if q and q[-1] not in ".!?":
+            q += "."
+    m = _TRAIL_EMAIL.search(q)
+    if m and m.group(1) in history_text:
+        q = q[:m.start()].rstrip()
+        if q and q[-1] not in ".!?":
+            q += "."
+    return q
+
+
+def _dedash(s):
+    if not s:
+        return s
+    return re.sub(r"\s+[-\u2013\u2014]\s+", ", ", s)
+
+
+def embed_host_turn(host):
+    """host history (small talk) + the host's own request rendered as a prior
+    tool turn (confuser-style encoding) + a confirmation. The embedded copy is
+    lightly humanized (preamble/auth-dedupe/dash cleanup); canonical host row is
+    not modified."""
+    h = [dict(m) for m in (host.get("history") or [])]
+    for m in h:                                   # T3: clean assistant dashes
+        if m.get("role") == "assistant" and m.get("content"):
+            m["content"] = _dedash(m["content"])
+    history_text = " ".join((m.get("content") or "") for m in h)
+    q = (host.get("query") or host.get("retrieval_text") or "").strip()
+    q = humanize_host_query(q, history_text)       # T1 + T2
+    h.append({"role": "user", "content": q, "tool_calls": [], "tool_call_id": None})
+    tcs = [{"name": c["name"], "arguments": c.get("arguments", {}),
+            "output": c.get("output"), "reasoning": c.get("reasoning", "")}
+           for c in host["calls"]]
+    h.append({"role": "assistant", "content": None, "tool_calls": tcs, "tool_call_id": None})
+    for c in host["calls"]:
+        h.append({"role": "tool", "content": c.get("output"), "tool_calls": [], "tool_call_id": None})
+    h.append({"role": "assistant", "content": _dedash(RND.choice(CONFIRM)), "tool_calls": [], "tool_call_id": None})
+    return h
+
+
+def history_tool_calls(host):
+    """Tool calls embedded in the host's own history (auth/reads retained earlier)."""
+    out = []
+    for m in (host.get("history") or []):
+        for tc in (m.get("tool_calls") or []):
+            out.append({"name": tc.get("name"), "arguments": tc.get("arguments", {}),
+                        "output": tc.get("output")})
+    return out
+
+
+# ------------------------------------------------ leaf/host value reconciliation
+def reconcile_leaf_with_host(calls, host):
+    """If the injected leaf reads an entity the host turn already established, copy
+    the host's recorded output verbatim so the same customer yields the same value
+    at the conversation level (and the row still reproduces in isolation)."""
+    leaf = calls[-1]
+    n = leaf["name"]
+    SELF = {"get_order_invoice", "get_shipping_options", "get_wishlist", "get_store_credit_balance"}
+    if n not in SELF:
+        return calls, None
+    a = leaf.get("arguments", {})
+    ent = ("#" + str(a["order_id"]).lstrip("#").upper()) if a.get("order_id") else a.get("user_id")
+
+    def _ent(c):
+        aa = c.get("arguments", {})
+        return ("#" + str(aa["order_id"]).lstrip("#").upper()) if aa.get("order_id") else aa.get("user_id")
+    for hc in host["calls"]:
+        if hc["name"] == n and _ent(hc) == ent and hc.get("output") is not None:
+            leaf["output"] = hc["output"]
+            return calls, (n, ent)
+    return calls, None
+
+
+# ------------------------------------------------ conversation-level state check
+def _ref_ids(call):
+    a = call.get("arguments", {}) or {}
+    out = {}
+    for k in ("user_id", "order_id", "gift_card_id"):
+        if a.get(k):
+            out[k] = a[k]
+    for k in ("item_id",):
+        if a.get(k):
+            out.setdefault("item_ids", []).append(a[k])
+    for k in ("item_ids", "new_item_ids"):
+        for v in (a.get(k) or []):
+            out.setdefault("item_ids", []).append(v)
+    return out
+
+
+def _establish(call, users, orders, items, cards):
+    n = call["name"]
+    raw = call.get("output")
+    o = parse(raw)
+    if n.startswith("find_user_id"):
+        uid = raw.strip().strip('"') if isinstance(raw, str) else None
+        if uid and "_" in uid:
+            users.add(uid)
+    elif n == "get_user_details" and o:
+        if o.get("user_id"):
+            users.add(o["user_id"])
+        for oid in (o.get("orders") or []):
+            orders.add("#" + str(oid).lstrip("#").upper())
+    elif n == "get_order_details" and o:
+        if o.get("order_id"):
+            orders.add("#" + str(o["order_id"]).lstrip("#").upper())
+        for it in (o.get("items") or []):
+            if it.get("item_id"):
+                items.add(str(it["item_id"]))
+    elif n == "get_gift_card_balance" and o and o.get("gift_card_id"):
+        cards.add(str(o["gift_card_id"]))
+    elif n == "get_wishlist" and o:
+        for it in (o.get("items") or []):
+            if isinstance(it, dict) and it.get("item_id"):
+                items.add(str(it["item_id"]))
+
+
+def conversation_state_check(seq_calls, catalog, hist_calls=()):
+    """Temporal grounding (no forward/unmarked refs) + output reproduction over the
+    whole merged conversation. ``hist_calls`` are tool calls from the host's history
+    (auth retained earlier), which pre-establish entities. Returns (forward_refs,
+    io_mismatches)."""
+    cat_orders = {"#" + str(o).lstrip("#").upper() for o in catalog.get("order_balances", {})}
+    cat_cards = {str(c) for c in catalog.get("gift_card_balances", {})}
+    users, orders, items, cards = set(), set(cat_orders), set(), set(cat_cards)
+    for hc in hist_calls:                      # entities established in host history
+        _establish(hc, users, orders, items, cards)
+    fwd = []
+    for i, c in enumerate(seq_calls):
+        refs = _ref_ids(c)
+        # user_id must be established, unless this call itself establishes it
+        # (find_user_id_* mints it; get_user_details is the auth-retained read).
+        if (refs.get("user_id") and refs["user_id"] not in users
+                and not c["name"].startswith("find_user_id")
+                and c["name"] != "get_user_details"):
+            fwd.append((i, c["name"], "user_id", refs["user_id"]))
+        if refs.get("order_id"):
+            oid = "#" + str(refs["order_id"]).lstrip("#").upper()
+            if oid not in orders and c["name"] != "get_order_details":
+                fwd.append((i, c["name"], "order_id", refs["order_id"]))
+        if refs.get("gift_card_id") and str(refs["gift_card_id"]) not in cards:
+            fwd.append((i, c["name"], "gift_card_id", refs["gift_card_id"]))
+        _establish(c, users, orders, items, cards)
+    # I/O reproduction over the merged sequence (progressive seed)
+    s = EpisodeState.from_trajectory({"calls": seq_calls}, catalog)
+    io = []
+    for c in seq_calls:
+        n = c["name"]
+        if n not in TOOLS:
+            continue
+        got = TOOLS[n](s, c.get("arguments", {}))
+        rec = parse(c.get("output"))
+        if n in G.FIND:
+            exp = (c.get("output") or "").strip().strip('"')
+            if got != exp:
+                io.append((n, "uid", got, exp))
+            continue
+        if not isinstance(rec, dict):
+            continue
+        if n in G.FULLMATCH:
+            if got != rec:
+                io.append((n, "dict-diff"))
+            continue
+        keys = G.CHECK.get(n, [])
+        if any(got.get(k) is None and rec.get(k) is not None for k in keys):
+            continue
+
+        def _eq(k):
+            g, rv = got.get(k), rec.get(k)
+            if k == "status" and isinstance(g, str) and isinstance(rv, str):
+                return g.replace(" ", "_") == rv.replace(" ", "_")
+            return g == rv
+        miss = [k for k in keys if not _eq(k)]
+        if miss:
+            io.append((n, {k: (got.get(k), rec.get(k)) for k in miss}))
+    return fwd, io
+
+
+# ------------------------------------------------------------------------- main
+def main():
+    asg = json.load(open(DATA / "_host_assignment.json", encoding="utf-8"))
+    c3 = [json.loads(l) for l in open(DATA / "c3_trajectories.jsonl", encoding="utf-8") if l.strip()]
+    byid = {r["example_id"]: r for r in c3}
+    cat_orders = ["#" + o.lstrip("#").upper() for o in CATALOG.get("order_balances", {})]
+    cat_cards = list(CATALOG.get("gift_card_balances", {}))
+
+    injected, prov = [], []
+    fails, merged = [], []
+    seq = 0
+    for a in asg:
+        host = byid[a["host"]]
+        u = host_customer(host, a)
+        oids = order_ids_for(a, u)
+        cat_order = a.get("grounded_cat_order") or RND.choice(cat_orders)
+        gift_card = a.get("grounded_card") or RND.choice(cat_cards)
+        prefix_tools = a["prefix"]
+        leaf = a["leaf"]
+        calls, primary = G.assemble(prefix_tools, leaf, u, oids, cat_order, gift_card)
+        calls, reconciled = reconcile_leaf_with_host(calls, host)
+        miss = G.verify_row(calls)
+        if miss:
+            fails.append((a["host"], leaf, miss))
+            continue
+
+        hist = embed_host_turn(host)
+        n_user = sum(1 for m in hist if m["role"] == "user")
+        turn_index = n_user + 1
+        total_turns = turn_index + RND.randint(1, 3)
+        position_norm = round(turn_index / max(total_turns, 1), 4)
+        tier = ("early" if position_norm < 0.34 else "middle" if position_norm < 0.67 else "late")
+        shown = cat_order if leaf in ("reorder_previous_order", "apply_gift_card") else primary
+        query = hq_variant(leaf, shown)
+        eid = f"confuser-{leaf}-minj{seq:03d}"
+        seq += 1
+
+        row = {
+            "example_id": eid, "query": query, "retrieval_text": query,
+            "calls": calls, "history": hist, "available_apis": None, "domain": "retail",
+            "metadata": {
+                "source": "synthetic", "distractor_class": "confuser", "model": "authored",
+                "confuser": leaf, "twin": False, "twin_of": None,
+                "anchor_state": list(prefix_tools), "anchor_depth": len(prefix_tools),
+                "hotspot": False, "synthetic_query": True, "tier": tier,
+                "turn_index": turn_index, "total_turns": total_turns,
+                "position_norm": position_norm, "embed_history": True,
+                "history": hist, "real_source": "authored-synthetic",
+            },
+        }
+        injected.append(row)
+        prov.append({"example_id": eid, "rebalance_node": a["node"], "confuser": leaf,
+                     "host_of": a["host"], "uid": a["uid"], "placement": "later-turn",
+                     "reconciled_leaf": reconciled})
+        merged.append((eid, host["calls"] + calls, history_tool_calls(host)))
+
+    (OUT / "_staging_merged_injections.jsonl").write_text(
+        "\n".join(json.dumps(r) for r in injected) + "\n", encoding="utf-8")
+    (OUT / "_merged_injections.prov.json").write_text(json.dumps(prov, indent=2), encoding="utf-8")
+
+    print(f"assembled {len(injected)}/51 injected rows (replay-verified)")
+    if fails:
+        print(f"ASSEMBLY/REPLAY FAILURES: {len(fails)}")
+        for f in fails[:20]:
+            print("   ", f)
+    tally = Counter((p["rebalance_node"], p["confuser"]) for p in prov)
+    for k in sorted(tally):
+        print("   ", k, tally[k])
+    print("   reconciled leaves (inherited host value):",
+          sum(1 for p in prov if p.get("reconciled_leaf")))
+
+    # ---- PASS 1: find unmarked variables across every merged conversation ----
+    made_up = {}
+    for eid, seq, hist in merged:
+        fwd, _ = conversation_state_check(seq, CATALOG, hist)
+        for (_i, tool, kind, val) in fwd:
+            if kind == "order_id":
+                oid = "#" + str(val).lstrip("#").upper()
+                if oid not in CATALOG["order_balances"]:
+                    # mark the host-intrinsic order in the CLONED free-running DB.
+                    made_up[oid] = {"order_balances": 0.01, "reason": f"{eid}:{tool} unread order"}
+    if made_up:
+        for oid, rec in made_up.items():
+            CATALOG.setdefault("order_balances", {})[oid.lstrip("#")] = rec["order_balances"]
+        (DATA / "catalog.json").write_text(json.dumps(CATALOG, indent=1), encoding="utf-8")
+        (OUT / "_made_up_values.json").write_text(json.dumps(made_up, indent=2), encoding="utf-8")
+
+    # ---- PASS 2: confirm the conversation is now fully marked + reproduces ----
+    fwd_all, io_all = [], []
+    for eid, seq, hist in merged:
+        fwd, io = conversation_state_check(seq, CATALOG, hist)
+        for f in fwd:
+            fwd_all.append((eid,) + f)
+        for m in io:
+            io_all.append((eid,) + (m if isinstance(m, tuple) else (m,)))
+
+    print(f"\nadded {len(made_up)} made-up var(s) to the cloned free-running DB")
+    print(f"CONVERSATION STATE CHECK (final): forward/unmarked refs = {len(fwd_all)} ; "
+          f"io mismatches = {len(io_all)}")
+    for x in fwd_all[:20]:
+        print("   FWD", x)
+    for x in io_all[:20]:
+        print("   IO ", x)
+    ok = not fails and not fwd_all and not io_all
+    print("\nRESULT:", "CLEAN" if ok else "NEEDS ATTENTION")
+    return 0 if ok else 1
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/tempscripts/injection_sandbox/run_c3.py b/tempscripts/injection_sandbox/run_c3.py
new file mode 100644
index 0000000000000000000000000000000000000000..8efe8efd89fe5eefa3572ef54cc9d2d607ad4f50
--- /dev/null
+++ b/tempscripts/injection_sandbox/run_c3.py
@@ -0,0 +1,109 @@
+"""SANDBOX C3 run: judge the 51 temp merged injections with the SAME procedure
+as the baseline run (single orientation, samples=3 majority, workers=4, model
+from datasetreview/config.yaml). Compares the injected caught-rate against the
+baseline overall rate and the 51 host rows' own baseline caught. Writes results
+only into the sandbox (out/c3_injected_results.jsonl); canonical files untouched.
+
+Run from repo root:  python -u temp/injection_sandbox/run_c3.py
+"""
+from __future__ import annotations
+
+import json
+import logging
+import random
+import sys
+from collections import Counter
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+
+import yaml
+
+for _n in ("azure", "azure.identity", "azure.core.pipeline.policies.http_logging_policy"):
+    logging.getLogger(_n).setLevel(logging.WARNING)
+
+ROOT = Path(__file__).resolve().parents[2]
+sys.path.insert(0, str(ROOT))
+
+from datasetreview import pipelines as P          # noqa: E402
+from datasetreview import judge_prompts as J       # noqa: E402
+from datasetreview.llm_client import make_judge     # noqa: E402
+
+SAND = Path(__file__).resolve().parent
+OUT = SAND / "out"
+MERGED = OUT / "_staging_merged_injections.jsonl"
+PROV = json.load(open(OUT / "_merged_injections.prov.json", encoding="utf-8"))
+BASELINE = ROOT / "datasetreview" / "results" / "new" / "C3.jsonl"
+
+cfg = yaml.safe_load(open(ROOT / "datasetreview" / "config.yaml", encoding="utf-8"))
+SAMPLES = 3          # baseline C3 used samples=3 majority
+WORKERS = cfg["run"].get("workers", 4)
+
+reals = P.real_trajectories()
+pairer = P.make_pairer(reals)
+judge = make_judge(cfg["model"])
+fakes = [json.loads(l) for l in open(MERGED, encoding="utf-8") if l.strip()]
+
+
+def judge_one(fake):
+    eid = fake["example_id"]
+    real = pairer(fake)
+    swap = random.Random(eid).random() < 0.5
+    msgs = J.build_c3(fake, real, swap=swap)
+    key = msgs["answer_key"]
+    guesses, err = [], None
+    for _ in range(SAMPLES):
+        try:
+            r = judge.judge({"system": msgs["system"], "user": msgs["user"]})
+            guesses.append(r.get("guess"))
+        except Exception as e:                 # noqa: BLE001
+            err = str(e)
+    if not guesses:
+        return {"example_id": eid, "error": err, "answer_key": key, "real_id": real.get("example_id")}
+    majority = Counter(guesses).most_common(1)[0][0]
+    agree = guesses.count(majority) / len(guesses)
+    return {"example_id": eid, "answer_key": key, "real_id": real.get("example_id"),
+            "guess": majority, "agreement": agree, "n_samples": len(guesses),
+            "sample_guesses": guesses, "caught": majority == key, "error": None}
+
+
+def main():
+    print(f"judging {len(fakes)} injected rows  (samples={SAMPLES}, workers={WORKERS}, "
+          f"model={cfg['model']['label']})")
+    with ThreadPoolExecutor(max_workers=WORKERS) as ex:
+        results = list(ex.map(judge_one, fakes))
+    results.sort(key=lambda r: r["example_id"])
+    (OUT / "c3_injected_results.jsonl").write_text(
+        "\n".join(json.dumps(r) for r in results) + "\n", encoding="utf-8")
+
+    ok = [r for r in results if r.get("error") is None and "caught" in r]
+    errs = [r for r in results if r.get("error") is not None or "caught" not in r]
+    caught = sum(1 for r in ok if r["caught"])
+    n = len(ok)
+
+    # baseline comparison
+    base = {}
+    for line in open(BASELINE, encoding="utf-8"):
+        if line.strip():
+            d = json.loads(line)
+            base[d.get("item_id")] = d.get("caught")
+    base_all = [v for v in base.values() if v is not None]
+    base_rate = sum(base_all) / len(base_all) if base_all else 0.0
+    host_of = {p["example_id"]: p["host_of"] for p in PROV}
+    host_caught = [base.get(host_of[r["example_id"]]) for r in ok]
+    host_caught = [v for v in host_caught if v is not None]
+    host_rate = sum(host_caught) / len(host_caught) if host_caught else 0.0
+
+    print("\n=== C3 RESULT (injected rows) ===")
+    print(f"  injected caught: {caught}/{n} = {caught/n:.1%}" if n else "  no valid results")
+    print(f"  errors: {len(errs)}")
+    print(f"\n  baseline overall (795 rows): {sum(base_all)}/{len(base_all)} = {base_rate:.1%}")
+    print(f"  the 51 hosts' own baseline caught: {sum(host_caught)}/{len(host_caught)} = {host_rate:.1%}")
+    delta = caught / n - base_rate if n else 0.0
+    print(f"\n  injected vs baseline-overall delta: {delta:+.1%}  "
+          f"(negative = injected fooled the judge MORE than baseline)")
+    print(f"  wrote out/c3_injected_results.jsonl")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/tempscripts/injection_sandbox/run_c3_big.py b/tempscripts/injection_sandbox/run_c3_big.py
new file mode 100644
index 0000000000000000000000000000000000000000..e537b884242c7a4530d73eb337c0f86d2614dc88
--- /dev/null
+++ b/tempscripts/injection_sandbox/run_c3_big.py
@@ -0,0 +1,141 @@
+"""SANDBOX C3 (large): position-invariant dual-orientation run over 102 items
+(51 humanized injected rows + their 51 host rows), samples=3 per orientation =
+612 judgments. Re-judging the hosts in THIS run makes before/after apples-to-apples
+(same judge instance, same pairing), removing run-to-run variance vs the stored
+baseline. Crash-safe: appends each finished item to out/c3_big_results.jsonl.
+Canonical files are read-only.
+
+Run from repo root:  python -u temp/injection_sandbox/run_c3_big.py
+"""
+from __future__ import annotations
+
+import json
+import logging
+import threading
+from collections import Counter
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+from statistics import mean
+
+import yaml
+
+for _n in ("azure", "azure.identity", "azure.core.pipeline.policies.http_logging_policy"):
+    logging.getLogger(_n).setLevel(logging.WARNING)
+
+import sys
+ROOT = Path(__file__).resolve().parents[2]
+sys.path.insert(0, str(ROOT))
+from datasetreview import pipelines as P          # noqa: E402
+from datasetreview import judge_prompts as J       # noqa: E402
+from datasetreview.llm_client import make_judge     # noqa: E402
+
+SAND = Path(__file__).resolve().parent
+OUT = SAND / "out"
+MERGED = OUT / "_staging_merged_injections.jsonl"
+PROV = json.load(open(OUT / "_merged_injections.prov.json", encoding="utf-8"))
+BASELINE = ROOT / "datasetreview" / "results" / "new" / "C3.jsonl"
+RESULTS = OUT / "c3_big_results.jsonl"
+
+cfg = yaml.safe_load(open(ROOT / "datasetreview" / "config.yaml", encoding="utf-8"))
+SAMPLES = 3
+
+reals = P.real_trajectories()
+pairer = P.make_pairer(reals)
+judge = make_judge(cfg["model"])
+
+injected = [json.loads(l) for l in open(MERGED, encoding="utf-8") if l.strip()]
+c3 = {r["example_id"]: r for r in
+      (json.loads(l) for l in open(SAND / "data" / "c3_trajectories.jsonl", encoding="utf-8") if l.strip())}
+host_of = {p["example_id"]: p["host_of"] for p in PROV}
+hosts = [c3[h] for h in dict.fromkeys(host_of.values())]   # unique, order-preserving
+
+items = ([("injected", r) for r in injected]
+         + [("host", r) for r in hosts])
+
+_lock = threading.Lock()
+_done = {}
+if RESULTS.exists():                               # resume support
+    for line in RESULTS.read_text(encoding="utf-8").splitlines():
+        if line.strip():
+            d = json.loads(line)
+            _done[(d["group"], d["example_id"])] = d
+
+
+def majority_guess(fake, real, swap):
+    msgs = J.build_c3(fake, real, swap=swap)
+    key = msgs["answer_key"]
+    gs = []
+    for _ in range(SAMPLES):
+        try:
+            gs.append(judge.judge({"system": msgs["system"], "user": msgs["user"]}).get("guess"))
+        except Exception:                          # noqa: BLE001
+            pass
+    if not gs:
+        return None, key, gs
+    return Counter(gs).most_common(1)[0][0], key, gs
+
+
+def run_item(group, fake):
+    eid = fake["example_id"]
+    if (group, eid) in _done:
+        return _done[(group, eid)]
+    real = pairer(fake)
+    per = {}
+    for name, swap in (("A", False), ("B", True)):   # fake in A, then fake in B
+        maj, key, gs = majority_guess(fake, real, swap)
+        per[name] = {"guess": maj, "answer_key": key, "caught": (maj == key), "samples": gs}
+    catches = [per["A"]["caught"], per["B"]["caught"]]
+    rec = {"group": group, "example_id": eid, "real_id": real.get("example_id"),
+           "order_avg_catch": mean(1.0 if c else 0.0 for c in catches),
+           "consistent_catch": all(catches), "any_catch": any(catches),
+           "A": per["A"], "B": per["B"]}
+    with _lock:
+        with open(RESULTS, "a", encoding="utf-8") as f:
+            f.write(json.dumps(rec) + "\n")
+    return rec
+
+
+def summarize(recs, group):
+    g = [r for r in recs if r["group"] == group]
+    n = len(g)
+    if not n:
+        return
+    oa = mean(r["order_avg_catch"] for r in g)
+    cons = sum(r["consistent_catch"] for r in g) / n
+    a_only = sum(r["A"]["caught"] for r in g) / n
+    print(f"  {group:9} n={n}  order-avg caught={oa:.1%}  "
+          f"consistent(both orders)={cons:.1%}  orientation-A caught={a_only:.1%}")
+
+
+def main():
+    todo = [it for it in items if (it[0], it[1]["example_id"]) not in _done]
+    print(f"items total={len(items)} (already done={len(_done)}) to-judge={len(todo)}  "
+          f"orientations=2 samples={SAMPLES}  -> ~{len(todo)*2*SAMPLES} live calls")
+    with ThreadPoolExecutor(max_workers=cfg["run"].get("workers", 4)) as ex:
+        list(ex.map(lambda it: run_item(*it), todo))
+
+    recs = [json.loads(l) for l in RESULTS.read_text(encoding="utf-8").splitlines() if l.strip()]
+    print("\n=== C3 LARGE RESULT (dual-orientation, samples=3 majority) ===")
+    summarize(recs, "injected")
+    summarize(recs, "host")
+
+    base = {}
+    for line in open(BASELINE, encoding="utf-8"):
+        if line.strip():
+            d = json.loads(line)
+            base[d.get("item_id")] = d.get("caught")
+    base_all = [v for v in base.values() if v is not None]
+    inj = [r for r in recs if r["group"] == "injected"]
+    hos = [r for r in recs if r["group"] == "host"]
+    print(f"\n  stored-baseline corpus (795): {sum(base_all)}/{len(base_all)} = {sum(base_all)/len(base_all):.1%}")
+    if inj and hos:
+        oi = mean(r["order_avg_catch"] for r in inj)
+        oh = mean(r["order_avg_catch"] for r in hos)
+        print(f"  same-run host order-avg caught:     {oh:.1%}")
+        print(f"  same-run injected order-avg caught: {oi:.1%}")
+        print(f"  injection+humanization effect (same hosts): {oi-oh:+.1%}")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/tempscripts/injection_sandbox/validate.py b/tempscripts/injection_sandbox/validate.py
new file mode 100644
index 0000000000000000000000000000000000000000..f8d273fa9e5732cb22ea6c4806af17d0e1ebc66b
--- /dev/null
+++ b/tempscripts/injection_sandbox/validate.py
@@ -0,0 +1,187 @@
+"""SANDBOX validation: logic tests + I/O tests over the 51 merged injected rows
+(each replayed together with its host turn). Reads only sandbox artifacts.
+
+Run: python -u temp/injection_sandbox/validate.py
+"""
+from __future__ import annotations
+
+import json
+import sys
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[2]
+SAND = Path(__file__).resolve().parent
+sys.path.insert(0, str(ROOT))
+sys.path.insert(0, str(ROOT / "systemUpgrade" / "executor"))
+
+import scripts._gen_injections2 as G          # noqa: E402
+from fake_state import EpisodeState           # noqa: E402
+from fake_tools import TOOLS                   # noqa: E402
+
+DATA = SAND / "data"
+OUT = SAND / "out"
+CATALOG = json.load(open(DATA / "catalog.json", encoding="utf-8"))
+G.CATALOG = CATALOG
+
+STRICT_PENDING = {"upgrade_shipping_speed", "modify_pending_order_items",
+                  "cancel_pending_order", "return_pending_order_items"}
+PRE_DELIVERY = {"schedule_delivery", "set_delivery_instructions", "get_shipping_options"}
+PENDING_OK = ("pending", "processing", "open", "pending (modified)")
+DELIVERED_OK = {"file_shipping_insurance_claim", "return_delivered_order_items",
+                "exchange_delivered_order_items"}
+BAD_STATUS = {"cancelled", "returned", "return requested"}
+
+
+def parse(o):
+    try:
+        return json.loads(o) if isinstance(o, str) and o.strip().startswith("{") else None
+    except json.JSONDecodeError:
+        return None
+
+
+def order_status_map(calls):
+    m = {}
+    for c in calls:
+        o = parse(c.get("output"))
+        if c["name"] == "get_order_details" and o and o.get("order_id"):
+            m["#" + str(o["order_id"]).lstrip("#").upper()] = (o.get("status") or "").lower()
+    return m
+
+
+def main():
+    inj = [json.loads(l) for l in open(OUT / "_staging_merged_injections.jsonl", encoding="utf-8") if l.strip()]
+    prov = json.load(open(OUT / "_merged_injections.prov.json", encoding="utf-8"))
+    c3 = {r["example_id"]: r for r in
+          (json.loads(l) for l in open(DATA / "c3_trajectories.jsonl", encoding="utf-8") if l.strip())}
+    host_of = {p["example_id"]: p["host_of"] for p in prov}
+
+    logic = {"open_status": [], "delivered_status": [], "acted_on_bad": [],
+             "modify_before_subscribe": [], "auth_before_use": []}
+    io = {"row_replay": [], "conv_replay": []}
+
+    for row in inj:
+        eid = row["example_id"]
+        calls = row["calls"]
+        host = c3[host_of[eid]]
+        merged = host["calls"] + calls
+        smap = order_status_map(merged)
+
+        # ---- LOGIC 1: order-status fit for the injected leaf/prefix ops ----
+        for c in calls:
+            n = c["name"]
+            oid = c.get("arguments", {}).get("order_id")
+            if not oid:
+                continue
+            oid = "#" + str(oid).lstrip("#").upper()
+            st = smap.get(oid)
+            if st is None:
+                continue
+            if n in STRICT_PENDING and st not in PENDING_OK:
+                logic["open_status"].append((eid, n, oid, st))
+            if n in PRE_DELIVERY and st not in PENDING_OK + ("shipped",):
+                logic["open_status"].append((eid, n, oid, st))
+            if n in DELIVERED_OK and st and st != "delivered":
+                logic["delivered_status"].append((eid, n, oid, st))
+            if st in BAD_STATUS:
+                logic["acted_on_bad"].append((eid, n, oid, st))
+
+        # ---- LOGIC 2: modify precedes subscribe (N3) ----
+        names = [c["name"] for c in calls]
+        if "subscribe_to_restock_alert" in names and "modify_pending_order_items" in names:
+            if names.index("modify_pending_order_items") > names.index("subscribe_to_restock_alert"):
+                logic["modify_before_subscribe"].append((eid, names))
+
+        # ---- LOGIC 3: auth/reads before use across the whole conversation ----
+        # Entities are established by the host's history tool calls and host turn
+        # first; the injected turn may legitimately act on them (later turn).
+        est_users, est_orders = set(), set()
+        cat_o = {"#" + str(x).lstrip("#").upper() for x in CATALOG.get("order_balances", {})}
+        hist_calls = []
+        for m in (host.get("history") or []):
+            for tc in (m.get("tool_calls") or []):
+                hist_calls.append({"name": tc.get("name"), "arguments": tc.get("arguments", {}),
+                                   "output": tc.get("output")})
+        for c in hist_calls + host["calls"]:      # pre-establish from prior turns
+            n = c["name"]
+            o = parse(c.get("output"))
+            if n.startswith("find_user_id"):
+                u = (c.get("output") or "").strip().strip('"')
+                if "_" in u:
+                    est_users.add(u)
+            if n == "get_user_details" and o and o.get("user_id"):
+                est_users.add(o["user_id"])
+            if n == "get_order_details" and o and o.get("order_id"):
+                est_orders.add("#" + str(o["order_id"]).lstrip("#").upper())
+        for c in calls:
+            n = c["name"]
+            a = c.get("arguments", {})
+            if a.get("user_id") and a["user_id"] not in est_users and not n.startswith("find_user_id") and n != "get_user_details":
+                logic["auth_before_use"].append((eid, n, "user_id", a["user_id"]))
+            if a.get("order_id"):
+                oo = "#" + str(a["order_id"]).lstrip("#").upper()
+                if oo not in est_orders and n != "get_order_details" and oo not in cat_o:
+                    logic["auth_before_use"].append((eid, n, "order_id", a["order_id"]))
+            o = parse(c.get("output"))
+            if n.startswith("find_user_id"):
+                u = (c.get("output") or "").strip().strip('"')
+                if "_" in u:
+                    est_users.add(u)
+            if n == "get_user_details" and o and o.get("user_id"):
+                est_users.add(o["user_id"])
+            if n == "get_order_details" and o and o.get("order_id"):
+                est_orders.add("#" + str(o["order_id"]).lstrip("#").upper())
+
+        # ---- IO 1: row-level replay (row's own calls reproduce) ----
+        if G.verify_row(calls):
+            io["row_replay"].append((eid, G.verify_row(calls)))
+
+        # ---- IO 2: conversation-level replay (host turn + injected turn) ----
+        s = EpisodeState.from_trajectory({"calls": merged}, CATALOG)
+        for c in merged:
+            n = c["name"]
+            if n not in TOOLS:
+                continue
+            got = TOOLS[n](s, c.get("arguments", {}))
+            rec = parse(c.get("output"))
+            if n in G.FIND:
+                if got != (c.get("output") or "").strip().strip('"'):
+                    io["conv_replay"].append((eid, n, "uid"))
+                continue
+            if not isinstance(rec, dict):
+                continue
+            if n in G.FULLMATCH:
+                if got != rec:
+                    io["conv_replay"].append((eid, n, "dict-diff"))
+                continue
+            keys = G.CHECK.get(n, [])
+            if any(got.get(k) is None and rec.get(k) is not None for k in keys):
+                continue
+
+            def _eq(k):
+                g, rv = got.get(k), rec.get(k)
+                if k == "status" and isinstance(g, str) and isinstance(rv, str):
+                    return g.replace(" ", "_") == rv.replace(" ", "_")
+                return g == rv
+            bad = [k for k in keys if not _eq(k)]
+            if bad:
+                io["conv_replay"].append((eid, n, {k: (got.get(k), rec.get(k)) for k in bad}))
+
+    print(f"validated {len(inj)} injected rows (each replayed with its host turn)\n")
+    print("=== LOGIC TESTS ===")
+    for k, v in logic.items():
+        print(f"  {k}: {len(v)} violation(s)")
+        for x in v[:8]:
+            print("      ", x)
+    print("\n=== I/O TESTS ===")
+    for k, v in io.items():
+        print(f"  {k}: {len(v)} mismatch(es)")
+        for x in v[:8]:
+            print("      ", x)
+
+    total = sum(len(v) for v in logic.values()) + sum(len(v) for v in io.values())
+    print("\nRESULT:", "ALL CLEAN" if total == 0 else f"{total} ISSUE(S)")
+    return 0 if total == 0 else 1
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/tempscripts/injection_sandbox/verify_trie.py b/tempscripts/injection_sandbox/verify_trie.py
new file mode 100644
index 0000000000000000000000000000000000000000..dc9380345ba0e4fd85e164f895dde0cbfec4b922
--- /dev/null
+++ b/tempscripts/injection_sandbox/verify_trie.py
@@ -0,0 +1,19 @@
+"""SANDBOX trie re-confirmation: rebuild the n100 trie WITHOUT and WITH the
+temp merged injections and report the 5 fix targets + LEAVE spine. Points the
+verifier's STAGING at temp/out/_staging_merged_injections.jsonl. Read-only.
+
+Run from repo root:  python -u temp/injection_sandbox/verify_trie.py
+"""
+from __future__ import annotations
+
+import sys
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[2]
+sys.path.insert(0, str(ROOT))
+sys.path.insert(0, str(ROOT / "systemUpgrade"))
+
+import scripts._verify_injection as V  # noqa: E402
+
+V.STAGING = Path(__file__).resolve().parent / "out" / "_staging_merged_injections.jsonl"
+raise SystemExit(V.main())
diff --git a/tempscripts/injection_sandbox/viz_trie.py b/tempscripts/injection_sandbox/viz_trie.py
new file mode 100644
index 0000000000000000000000000000000000000000..a78b1fc3ebe0de3be1fbafa4270fd66a6edcdfb2
--- /dev/null
+++ b/tempscripts/injection_sandbox/viz_trie.py
@@ -0,0 +1,124 @@
+"""SANDBOX trie visualization: build the n100 execution trie over canonical
+train + test + synthetic + the 51 temp merged injections, and emit into the
+sandbox out/ folder:
+  - trie_after.txt        full highlighted text tree
+  - trie_targets.txt      focused before/after view of the 5 fix-target nodes
+  - trie_after.png/.svg   rendered image (if Graphviz is installed)
+Read-only w.r.t. canonical data.
+
+Run from repo root:  python -u temp/injection_sandbox/viz_trie.py
+"""
+from __future__ import annotations
+
+import json
+import sys
+from collections import Counter
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[2]
+sys.path.insert(0, str(ROOT))
+sys.path.insert(0, str(ROOT / "systemUpgrade"))
+
+from pipeline import load_examples                       # noqa: E402
+from trie.builder import build_trie                      # noqa: E402
+from scripts.visualize_distractor_trie import _render_image  # noqa: E402
+
+SAND = Path(__file__).resolve().parent
+OUT = SAND / "out"
+EXP = ROOT / "data" / "tau-2" / "processed_distractor_exp2"
+N100 = EXP / "n100"
+MERGED = OUT / "_staging_merged_injections.jsonl"
+
+TARGETS = {
+    "N1": ["find_user_id_by_email"],
+    "N2": ["find_user_id_by_email", "get_user_details"],
+    "N3": ["modify_pending_order_items"],
+    "N4": ["find_user_id_by_name_zip", "get_user_details",
+           "get_order_details", "get_order_details",
+           "get_order_details", "get_order_details"],
+    "N5": ["find_user_id_by_name_zip", "get_order_details"],
+}
+
+manifest = json.loads((N100 / "apis.manifest.json").read_text(encoding="utf-8"))
+REAL, CONF, DUMMY = set(manifest.get("real", [])), set(manifest.get("confuser", [])), set(manifest.get("dummy", []))
+
+
+def cls(name):
+    return "REAL" if name in REAL else "conf" if name in CONF else "dummy" if name in DUMMY else "?"
+
+
+def build(with_merged):
+    ex = load_examples(EXP / "train.jsonl") + load_examples(EXP / "test.jsonl")
+    ex += load_examples(N100 / "synthetic_trajectories.jsonl")
+    if with_merged:
+        ex += load_examples(MERGED)
+    return build_trie(ex)
+
+
+def target_view(trie):
+    lines = []
+    for name, path in TARGETS.items():
+        node = trie.traverse(tuple(path))
+        lines.append(f"\n{name}  {' > '.join(path)}")
+        if node is None or node.total_child_count() == 0:
+            lines.append("   (absent)")
+            continue
+        probs = node.transition_probs()
+        for nm in sorted(node.children, key=lambda n: -probs[n]):
+            tag = cls(nm)
+            mark = ">>" if tag == "REAL" else "  "
+            lines.append(f"   {mark} [{tag:5}] {nm:32} p={probs[nm]:.3f}  count={node.children[nm].count}")
+    return lines
+
+
+def main():
+    before, after = build(False), build(True)
+
+    # focused before/after target view
+    tv = ["FIX-TARGET NODES  (before vs after temp injection)", "=" * 70]
+    tv.append("\n--- BEFORE ---")
+    tv += target_view(before)
+    tv.append("\n\n--- AFTER (with 51 merged injections) ---")
+    tv += target_view(after)
+    (OUT / "trie_targets.txt").write_text("\n".join(tv), encoding="utf-8")
+
+    # full highlighted text tree (after)
+    lines, node_cls, stats = [], Counter(), {"nodes": 0, "max_depth": 0}
+
+    def render(node, depth):
+        for child in sorted(node.children.values(), key=lambda c: (-c.count, c.api_name)):
+            c = cls(child.api_name)
+            node_cls[c] += 1
+            stats["nodes"] += 1
+            stats["max_depth"] = max(stats["max_depth"], depth + 1)
+            ind = "    " * depth
+            if c == "REAL":
+                lines.append(f"{ind}>> REAL  {child.api_name}  (count={child.count})")
+            else:
+                lines.append(f"{ind}   [{c:5}] {child.api_name}  (count={child.count})")
+            render(child, depth + 1)
+
+    render(after.root, 0)
+    header = [
+        "EXP2 EXECUTION TRIE  (train + test + synthetic + 51 temp injections)",
+        "=" * 70,
+        f"trajectories: before={before.root.count}  after={after.root.count}  "
+        f"(+{after.root.count - before.root.count})",
+        f"trie nodes: {stats['nodes']}   max depth: {stats['max_depth']}",
+        "nodes by class: " + "  ".join(f"{k}={node_cls[k]}" for k in ("REAL", "conf", "dummy", "?")),
+        "Legend: '>> REAL' = real tau2 API;  [conf] = confuser;  [dummy] = off-domain",
+        "=" * 70, "",
+    ]
+    (OUT / "trie_after.txt").write_text("\n".join(header + lines), encoding="utf-8")
+
+    img = _render_image(after.root, cls, OUT / "trie_after", fmt="png")
+    _render_image(after.root, cls, OUT / "trie_after", fmt="svg")
+
+    print(f"trajectories before={before.root.count} after={after.root.count} (+{after.root.count-before.root.count})")
+    print("wrote:", (OUT / 'trie_targets.txt').name, ",", (OUT / 'trie_after.txt').name,
+          ("," + Path(img).name if img else "(no image: Graphviz not installed)"))
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/tempscripts/story_remediation/add_turns/build_v2.py b/tempscripts/story_remediation/add_turns/build_v2.py
new file mode 100644
index 0000000000000000000000000000000000000000..0cd36043c0260ad01df97be75baac2d56667ff69
--- /dev/null
+++ b/tempscripts/story_remediation/add_turns/build_v2.py
@@ -0,0 +1,199 @@
+"""Build the ADD-TURNS v2 dataset (temp only).
+
+Base = wording-remediation applied where we have it:
+  full-795 = {514 remediated rows} UNION {281 untouched originals}
+
+Intervention = splice ONE logic-safe tool-call turn into `history` for the
+eligible ~19% (never touching `query` or `calls`):
+  * authed-in-history rows  -> reuse the row's OWN recorded get_order_details
+    output as an "open the order" beat AFTER auth (no re-auth, zero fabrication).
+    Fallback to the catalog browse if the row has no get_order_details.
+  * opener / no-auth rows    -> an auth-free list_all_product_types browse turn
+    (real tool, no entity, valid before auth). Output reused verbatim from a real
+    tau2 trajectory.
+
+C3 only renders HISTORY tool markers, so this is the only place an added tool
+turn is visible; the harvested turn's calls (the retrieval target) stay fixed.
+
+Writes add_turns/out/trajectories_v2.jsonl + prints eligibility + effect stats.
+Run: python -u temp/story_remediation/add_turns/build_v2.py
+"""
+from __future__ import annotations
+import json, sys
+from collections import Counter
+from pathlib import Path
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+sys.path.insert(0, str(ROOT))
+from datasetreview import pipelines as P  # noqa: E402
+
+N100 = ROOT / "distractor_generation_2" / "datasets" / "n100" / "trajectories.jsonl"
+REMED = ROOT / "temp" / "story_remediation" / "out" / "trajectories_remediated.jsonl"
+OUT = HERE / "out" / "trajectories_v2.jsonl"
+
+AUTH_FIND = {"find_user_id_by_email", "find_user_id_by_name_zip",
+             "find_user_id_by_phone", "find_user_id_by_username"}
+
+
+def parse(o):
+    try:
+        return json.loads(o) if isinstance(o, str) else o
+    except Exception:
+        return None
+
+
+def _out_str(o):
+    return o if isinstance(o, str) else json.dumps(o, ensure_ascii=False)
+
+
+def hist_call_names(r):
+    hist = r.get("history") or (r.get("metadata") or {}).get("history") or []
+    return [tc.get("name") for m in hist for tc in (m.get("tool_calls") or [])]
+
+
+def orders_of(r):
+    for c in (r.get("calls") or []):
+        if c["name"] == "get_user_details":
+            o = parse(c.get("output"))
+            if isinstance(o, dict):
+                return o.get("orders") or []
+    return []
+
+
+def touched_orders(r):
+    t = set()
+    for c in (r.get("calls") or []):
+        for v in (c.get("arguments") or {}).values():
+            if isinstance(v, str) and v.startswith("#W"):
+                t.add(v)
+    return t
+
+
+def first_order_read(r):
+    """First get_order_details call (history or current) with a dict output -> (oid, status, output_str)."""
+    seqs = list(r.get("calls") or [])
+    for m in (r.get("history") or (r.get("metadata") or {}).get("history") or []):
+        seqs.extend(m.get("tool_calls") or [])
+    for c in seqs:
+        if c.get("name") == "get_order_details":
+            o = parse(c.get("output"))
+            if isinstance(o, dict) and o.get("order_id"):
+                return o["order_id"], o.get("status"), _out_str(o)
+    return None
+
+
+# real list_all_product_types output (verbatim from a real tau2 trajectory)
+_LPT = None
+for _r in P.real_trajectories():
+    for _c in (_r.get("calls") or []):
+        if _c["name"] == "list_all_product_types" and _c.get("output"):
+            _LPT = _out_str(_c["output"]); break
+    if _LPT:
+        break
+assert _LPT, "no real list_all_product_types output found"
+
+_AUTHED_Q = [
+    "Before we get into it, can you pull up {oid} so I can see where it stands?",
+    "First, could you open my order {oid} for me?",
+    "Can you take a look at {oid} while you have my account up?",
+    "One sec, mind pulling up {oid} so we're both looking at the same thing?",
+]
+_CATALOG_Q = [
+    "Quick thing first, what kinds of products do you carry?",
+    "Before that, what product categories do you have these days?",
+    "Out of curiosity, what sorts of things do you sell?",
+    "First, can you tell me what product types you stock?",
+]
+_CATALOG_A = ("We carry a pretty wide range, electronics, home, fitness, and more. "
+              "Anyway, what can I help you with?")
+
+
+def add_block(r, kind, idx):
+    v = idx % 4
+    if kind == "authed":
+        rd = first_order_read(r)
+        if rd:
+            oid, status, out_str = rd
+            stxt = f"It's currently {status}." if status else "I've got it open."
+            return [
+                {"role": "user", "content": _AUTHED_Q[v].format(oid=oid),
+                 "tool_calls": [], "tool_call_id": None},
+                {"role": "assistant", "content": None,
+                 "tool_calls": [{"name": "get_order_details", "arguments": {"order_id": oid},
+                                 "output": out_str, "reasoning": "Opening the order to check its status."}],
+                 "tool_call_id": None},
+                {"role": "tool", "content": out_str, "tool_calls": [], "tool_call_id": None},
+                {"role": "assistant", "content": f"Sure, {oid}, {stxt}",
+                 "tool_calls": [], "tool_call_id": None},
+            ]
+        kind = "catalog"  # fallback
+    # catalog browse (auth-free)
+    return [
+        {"role": "user", "content": _CATALOG_Q[v], "tool_calls": [], "tool_call_id": None},
+        {"role": "assistant", "content": None,
+         "tool_calls": [{"name": "list_all_product_types", "arguments": {},
+                         "output": _LPT, "reasoning": "Listing available product categories."}],
+         "tool_call_id": None},
+        {"role": "tool", "content": _LPT, "tool_calls": [], "tool_call_id": None},
+        {"role": "assistant", "content": _CATALOG_A, "tool_calls": [], "tool_call_id": None},
+    ]
+
+
+def main():
+    orig = {json.loads(l)["example_id"]: json.loads(l) for l in open(N100, encoding="utf-8") if l.strip()}
+    remed = {json.loads(l)["example_id"]: json.loads(l) for l in open(REMED, encoding="utf-8") if l.strip()}
+    base = {eid: remed.get(eid, orig[eid]) for eid in orig}  # full 795, wording where available
+
+    cat = Counter(); applied = Counter(); changed = []
+    rows_out = []
+    for i, (eid, r) in enumerate(sorted(base.items())):
+        r = json.loads(json.dumps(r))  # deep copy
+        cn = [c["name"] for c in (r.get("calls") or [])]
+        hn = hist_call_names(r)
+        cur_auth = any(x in AUTH_FIND for x in cn)
+        hist_auth = any(x in AUTH_FIND for x in hn) or ("get_user_details" in hn)
+        orders = orders_of(r); unt = [o for o in orders if o not in touched_orders(r)]
+        kind = None
+        if hist_auth and not cur_auth:
+            cat["authed-in-history"] += 1; kind = "authed"
+        elif not cur_auth and not hist_auth:
+            cat["no-auth"] += 1; kind = "catalog"
+        elif cur_auth and len(unt) >= 1:
+            cat["opener-untouched"] += 1; kind = "catalog"
+        else:
+            cat["opener-all-touched (skip)"] += 1
+
+        if kind:
+            hist = list(r.get("history") or (r.get("metadata") or {}).get("history") or [])
+            block = add_block(r, kind, i)
+            new_hist = hist + block  # append just before the harvested turn
+            r["history"] = new_hist
+            if r.get("metadata"):
+                r["metadata"]["history"] = new_hist
+            applied[block[1]["tool_calls"][0]["name"]] += 1
+            changed.append(eid)
+        rows_out.append(r)
+
+    OUT.parent.mkdir(parents=True, exist_ok=True)
+    with OUT.open("w", encoding="utf-8") as fh:
+        for r in rows_out:
+            fh.write(json.dumps(r, ensure_ascii=False) + "\n")
+    (HERE / "out" / "changed_ids.txt").write_text("\n".join(changed) + "\n", encoding="utf-8")
+
+    print(f"base rows        : {len(rows_out)}")
+    print(f"eligibility      : {dict(cat)}")
+    print(f"rows changed     : {len(changed)}")
+    print(f"added tool by type: {dict(applied)}")
+    # effect: turns-with-tool-call before/after on changed rows
+    def tt(r):
+        return sum(1 for m in (r.get("history") or []) if m.get("tool_calls")) + (1 if r.get("calls") else 0)
+    before = [tt(base[e]) for e in changed]
+    after = [tt(next(x for x in rows_out if x["example_id"] == e)) for e in changed]
+    import statistics as st
+    print(f"changed rows tool-call turns: before mean {st.mean(before):.2f} -> after mean {st.mean(after):.2f}")
+    print(f"wrote {OUT.relative_to(ROOT)}  + out/changed_ids.txt")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/add_turns/replay_v2.py b/tempscripts/story_remediation/add_turns/replay_v2.py
new file mode 100644
index 0000000000000000000000000000000000000000..be09ab0b4ebe1ef26be8242222b5f92b6bf9aafc
--- /dev/null
+++ b/tempscripts/story_remediation/add_turns/replay_v2.py
@@ -0,0 +1,151 @@
+"""Free-running state runthrough on the REMEDIATED trajectories.
+
+Reuses the exact executor (fake_state + fake_tools + catalog) from
+systemUpgrade/executor, but seeds/replays from our remediated file. Since the
+remediation changed ONLY dialogue (history + query) and never `calls`, this must
+reproduce recorded outputs at the same rate as baseline -- any new mismatch/EXC
+would be a logic or I/O regression introduced by the rewrite.
+
+Also cross-checks each remediated row's calls are byte-identical to the source
+n100 row (proves no floating vars / dropped IDs leaked into calls).
+
+Run from repo root: python -u temp/story_remediation/replay_remediated.py
+"""
+from __future__ import annotations
+import json, sys
+from collections import Counter, defaultdict
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[3]
+EXEC = ROOT / "systemUpgrade" / "executor"
+sys.path.insert(0, str(EXEC))
+from fake_state import EpisodeState        # noqa: E402
+from fake_tools import TOOLS               # noqa: E402
+
+catalog = json.load(open(EXEC / "catalog.json", encoding="utf-8"))
+REMED = ROOT / "temp" / "story_remediation" / "add_turns" / "out" / "trajectories_v2.jsonl"
+SRC = ROOT / "distractor_generation_2" / "datasets" / "n100" / "trajectories.jsonl"
+
+rem = [json.loads(l) for l in open(REMED, encoding="utf-8") if l.strip()]
+src = {json.loads(l)["example_id"]: json.loads(l)
+       for l in open(SRC, encoding="utf-8") if l.strip()}
+
+# 1) calls integrity: remediated calls must equal source calls exactly
+calls_diff = [r["example_id"] for r in rem
+              if json.dumps(r["calls"], sort_keys=True) != json.dumps(src[r["example_id"]]["calls"], sort_keys=True)]
+
+# reuse replay.py's CHECK/FULLMATCH/FIND config
+import importlib.util
+spec = importlib.util.spec_from_file_location("_replay", EXEC / "replay.py")
+# can't exec replay.py (it runs on import); inline the needed maps instead:
+FULLMATCH = {"get_product_details", "get_size_guide", "get_product_reviews", "get_item_details",
+             "get_warranty_details", "get_extended_warranty_options", "get_shipping_options",
+             "get_active_promotions", "list_all_product_types", "get_user_reviews", "get_order_invoice"}
+FIND = {"find_user_id_by_email", "find_user_id_by_phone", "find_user_id_by_username", "find_user_id_by_name_zip"}
+CHECK = {
+    "apply_gift_card": ["amount_applied", "remaining_balance_due"], "apply_discount_code": ["discount", "status"],
+    "checkout_cart": ["total"], "cancel_order_item": ["status", "item_id"],
+    "return_pending_order_items": ["status", "item_ids"], "return_delivered_order_items": ["status", "item_ids"],
+    "exchange_delivered_order_items": ["status"], "modify_pending_order_items": [],
+    "remove_item_from_cart": ["subtotal"], "add_item_to_cart": ["user_id"], "get_order_details": ["status"],
+    "get_user_details": ["user_id", "email"], "get_cart_contents": ["subtotal"], "get_gift_card_balance": ["balance"],
+    "get_loyalty_points_balance": ["points"], "get_store_credit_balance": ["balance"], "get_wishlist": ["items"],
+    "cancel_delivered_order": ["status", "refund"], "cancel_pending_order": ["status", "refund"],
+    "modify_pending_order_address": ["status"], "add_gift_message": ["gift_message"],
+    "schedule_delivery": ["scheduled_delivery", "status"], "set_delivery_instructions": ["delivery_instructions", "status"],
+    "schedule_installation": ["appointment_id"], "book_repair_appointment": ["appointment_id"],
+    "request_return_pickup": ["confirmation"], "get_return_label": ["label_url"],
+    "request_gift_receipt": ["gift_receipt_url", "prices_shown"],
+    "file_shipping_insurance_claim": ["claim_id", "status", "estimated_review_days"],
+    "upgrade_shipping_speed": ["shipping_speed", "status"], "split_order_shipment": ["status"],
+    "request_price_adjustment": ["status"], "request_price_match": ["item_id"],
+    "reorder_previous_order": ["duplicated_from", "status", "total"], "register_product_warranty": [],
+    "submit_product_review": [], "subscribe_to_restock_alert": [], "redeem_loyalty_points": ["points_redeemed", "credit"],
+    "purchase_gift_card": ["amount"], "add_to_wishlist": ["user_id"], "modify_user_email": ["status", "email"],
+    "modify_user_name": ["status"], "modify_user_phone": ["status", "phone"], "update_user_password": ["status"],
+    "add_user_address": ["status"], "modify_user_address": ["status"], "delete_user_address": ["status", "deleted_zip"],
+    "verify_user_identity": ["verified"],
+}
+
+
+def parse(o):
+    try:
+        return json.loads(o) if isinstance(o, str) else o
+    except json.JSONDecodeError:
+        return None
+
+
+stats = defaultdict(lambda: {"n": 0, "match": 0, "skip_nodata": 0, "mism": [], "exc": []})
+covered, uncovered = Counter(), Counter()
+
+for r in rem:
+    s = EpisodeState.from_trajectory(r, catalog)
+    for c in r["calls"]:
+        n = c["name"]
+        if n not in TOOLS:
+            uncovered[n] += 1
+            continue
+        covered[n] += 1
+        rec = parse(c.get("output"))
+        st = stats[n]
+        st["n"] += 1
+        try:
+            got = TOOLS[n](s, c.get("arguments", {}))
+        except Exception as e:  # noqa
+            st["exc"].append((r["example_id"], f"{type(e).__name__}: {e}"))
+            continue
+        if n in FIND:
+            if got == (c.get("output") or "").strip().strip('"'):
+                st["match"] += 1
+            else:
+                st["mism"].append((r["example_id"], {"uid": (got, c.get("output"))}))
+            continue
+        if not isinstance(rec, dict):
+            st["match"] += 1
+            continue
+        if n in FULLMATCH:
+            st["match"] += 1 if got == rec else st["mism"].append((r["example_id"], "dict-diff"))
+            if got == rec:
+                pass
+            continue
+        keys = CHECK.get(n, [])
+        if any(got.get(k) is None and rec.get(k) is not None for k in keys):
+            st["skip_nodata"] += 1
+            continue
+
+        def _eq(k):
+            g, rv = got.get(k), rec.get(k)
+            if k == "status" and isinstance(g, str) and isinstance(rv, str):
+                return g.replace(" ", "_") == rv.replace(" ", "_")
+            return g == rv
+        if all(_eq(k) for k in keys):
+            st["match"] += 1
+        else:
+            st["mism"].append((r["example_id"], {k: (got.get(k), rec.get(k)) for k in keys if not _eq(k)}))
+
+tot_chk = sum(st["n"] - st["skip_nodata"] for st in stats.values())
+tot_match = sum(st["match"] for st in stats.values())
+tot_exc = sum(len(st["exc"]) for st in stats.values())
+tot_mism = sum(len(st["mism"]) for st in stats.values())
+tot_skip = sum(st["skip_nodata"] for st in stats.values())
+
+print("=== CALLS INTEGRITY (remediated vs source n100) ===")
+print(f"  rows: {len(rem)}   calls differ from source: {len(calls_diff)}  {calls_diff[:5]}")
+print("\n=== FREE-RUNNING REPLAY (remediated trajectories) ===")
+print(f"  reproduced : {tot_match}/{tot_chk} = {tot_match/max(tot_chk,1):.1%}")
+print(f"  exceptions : {tot_exc}")
+print(f"  mismatches : {tot_mism}")
+print(f"  skipped-no-seed : {tot_skip}")
+print(f"  tools implemented/exercised : {len(stats)}   uncovered(echo) calls: {sum(uncovered.values())}")
+if tot_exc:
+    print("\n  -- EXCEPTIONS --")
+    for n, st in sorted(stats.items()):
+        for eid, msg in st["exc"][:5]:
+            print(f"    [{n}] {eid}: {msg}")
+if tot_mism:
+    print("\n  -- MISMATCHES --")
+    for n, st in sorted(stats.items()):
+        for eid, d in st["mism"][:5]:
+            print(f"    [{n}] {eid}: {d}")
+
+
diff --git a/tempscripts/story_remediation/add_turns/run_c3_v2.py b/tempscripts/story_remediation/add_turns/run_c3_v2.py
new file mode 100644
index 0000000000000000000000000000000000000000..67b3fcbaba937fa85852ba2260363dfbd609d7a0
--- /dev/null
+++ b/tempscripts/story_remediation/add_turns/run_c3_v2.py
@@ -0,0 +1,109 @@
+"""Run C3 on the remediated trajectories and compare to baseline.
+
+Same judge procedure as the baseline C3 pass (samples=3 majority, workers from
+config, model from datasetreview/config.yaml). For a controlled before/after we
+reuse each row's BASELINE pairing + orientation (answer_key) so the ONLY thing
+that changed is the remediated dialogue.
+
+Writes out/C3_remediated.jsonl (canonical files untouched).
+Run from repo root:  python -u temp/story_remediation/run_c3_remediated.py
+"""
+from __future__ import annotations
+import json, logging, sys
+from collections import Counter
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+import yaml
+
+for _n in ("azure", "azure.identity", "azure.core.pipeline.policies.http_logging_policy"):
+    logging.getLogger(_n).setLevel(logging.WARNING)
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+sys.path.insert(0, str(ROOT))
+
+from datasetreview import pipelines as P            # noqa: E402
+from datasetreview import judge_prompts as J        # noqa: E402
+from datasetreview.llm_client import make_judge      # noqa: E402
+
+OUT = HERE / "out"
+REMED = OUT / "trajectories_v2.jsonl"
+BASELINE = ROOT / "datasetreview" / "results" / "new" / "C3.jsonl"
+RESULT = OUT / "C3_v2.jsonl"
+
+cfg = yaml.safe_load(open(ROOT / "datasetreview" / "config.yaml", encoding="utf-8"))
+SAMPLES = 3
+WORKERS = max(8, cfg["run"].get("workers", 4))
+
+base = {}
+for line in open(BASELINE, encoding="utf-8"):
+    if line.strip():
+        d = json.loads(line)
+        base[d["item_id"]] = d
+
+reals = P.real_trajectories()
+pairer = P.make_pairer(reals)
+judge = make_judge(cfg["model"])
+fakes = [json.loads(l) for l in open(REMED, encoding="utf-8") if l.strip()]
+
+
+def judge_one(fake):
+    eid = fake["example_id"]
+    b = base.get(eid)
+    real = pairer(fake)
+    # reuse baseline orientation: answer_key A => swap False, B => swap True
+    swap = (b or {}).get("answer_key") == "B"
+    msgs = J.build_c3(fake, real, swap=swap)
+    key = msgs["answer_key"]
+    guesses, err = [], None
+    for _ in range(SAMPLES):
+        try:
+            r = judge.judge({"system": msgs["system"], "user": msgs["user"]})
+            guesses.append(r.get("guess"))
+        except Exception as e:  # noqa: BLE001
+            err = str(e)
+    if not guesses:
+        return {"item_id": eid, "error": err, "answer_key": key,
+                "real_id": real.get("example_id")}
+    majority = Counter(guesses).most_common(1)[0][0]
+    agree = guesses.count(majority) / len(guesses)
+    return {"item_id": eid, "answer_key": key, "real_id": real.get("example_id"),
+            "baseline_real_id": (b or {}).get("real_id"),
+            "guess": majority, "agreement": agree, "n_samples": len(guesses),
+            "sample_guesses": guesses, "caught": majority == key,
+            "baseline_caught": (b or {}).get("caught"), "error": None}
+
+
+def main():
+    print(f"judging {len(fakes)} remediated rows (samples={SAMPLES}, workers={WORKERS}, "
+          f"model={cfg['model']['label']})")
+    with ThreadPoolExecutor(max_workers=WORKERS) as ex:
+        results = list(ex.map(judge_one, fakes))
+    results.sort(key=lambda r: r["item_id"])
+    RESULT.write_text("\n".join(json.dumps(r) for r in results) + "\n", encoding="utf-8")
+
+    ok = [r for r in results if r.get("error") is None and "caught" in r]
+    errs = [r for r in results if r.get("error") is not None or "caught" not in r]
+    caught = sum(1 for r in ok if r["caught"])
+    n = len(ok)
+    base_caught = sum(1 for r in ok if r.get("baseline_caught"))
+    pair_match = sum(1 for r in ok if r.get("real_id") == r.get("baseline_real_id"))
+    flip_fixed = sum(1 for r in ok if r.get("baseline_caught") and not r["caught"])
+    flip_regress = sum(1 for r in ok if not r.get("baseline_caught") and r["caught"])
+
+    print("\n=== C3 V2 (ADD-TURNS) RESULT ===")
+    print(f"  rows judged        : {n}   errors: {len(errs)}")
+    print(f"  pairing match base : {pair_match}/{n}")
+    print(f"  baseline caught    : {base_caught}/{n} = {base_caught/n:.1%}")
+    print(f"  remediated caught  : {caught}/{n} = {caught/n:.1%}")
+    print(f"  fixed (caught->fooled)   : {flip_fixed}")
+    print(f"  regressed (fooled->caught): {flip_regress}")
+    print(f"  wrote {RESULT.relative_to(ROOT)}")
+    if errs:
+        print("  sample error:", errs[0].get("error"))
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
+
diff --git a/tempscripts/story_remediation/analyze_caught.py b/tempscripts/story_remediation/analyze_caught.py
new file mode 100644
index 0000000000000000000000000000000000000000..6fb3057051f310d32dd2aad7cdaef358d96a3bb5
--- /dev/null
+++ b/tempscripts/story_remediation/analyze_caught.py
@@ -0,0 +1,107 @@
+"""Capture C3 reasoning for the STILL-CAUGHT remediated rows, then bucket the
+tells so we can see what C3 is still catching them on.
+
+Rebuilds the exact same prompt/orientation used in the scored run (baseline
+answer_key), calls the judge once per row for its reasoning, writes
+out/C3_remediated_caught_reasons.jsonl, and prints a tell-bucket histogram.
+
+Run: python -u temp/story_remediation/analyze_caught.py
+"""
+from __future__ import annotations
+import json, logging, re, sys
+from collections import Counter
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+import yaml
+
+for _n in ("azure", "azure.identity", "azure.core.pipeline.policies.http_logging_policy"):
+    logging.getLogger(_n).setLevel(logging.WARNING)
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[1]
+sys.path.insert(0, str(ROOT))
+from datasetreview import pipelines as P            # noqa: E402
+from datasetreview import judge_prompts as J        # noqa: E402
+from datasetreview.llm_client import make_judge      # noqa: E402
+
+OUT = HERE / "out"
+cfg = yaml.safe_load(open(ROOT / "datasetreview" / "config.yaml", encoding="utf-8"))
+base = {json.loads(l)["item_id"]: json.loads(l)
+        for l in open(ROOT / "datasetreview" / "results" / "new" / "C3.jsonl", encoding="utf-8") if l.strip()}
+remed = {r["example_id"]: r for r in
+         (json.loads(l) for l in open(OUT / "trajectories_remediated.jsonl", encoding="utf-8") if l.strip())}
+scored = {json.loads(l)["item_id"]: json.loads(l)
+          for l in open(OUT / "C3_remediated.jsonl", encoding="utf-8") if l.strip()}
+caught_ids = [iid for iid, r in scored.items() if r.get("caught")]
+
+reals = P.real_trajectories()
+pairer = P.make_pairer(reals)
+judge = make_judge(cfg["model"])
+
+# tell buckets -> keyword patterns matched against reasoning about the fake side
+BUCKETS = {
+    "bundled_multitask":   r"multi[- ]?task|multiple (distinct|separate) |several (distinct|requests)|checklist|enumerat|packs|laundry list|bundl",
+    "too_precise_ids":     r"exact (order|id|item)|precise|order number|conveniently|front[- ]?load|all the details|specific ids|recites|recite",
+    "no_backforth_dense":  r"no back[- ]?and[- ]?forth|dense|rapid|single (turn|message)|one (turn|message|go)|without (any )?clarif|immediately|right away|opening (message|turn)",
+    "invented_capability": r"unusual (request|task|service)|would not (typically|normally)|no real|not (a )?(typical|standard|common)|niche|obscure|rare (request|service)|atypical",
+    "agent_overconfident": r"agent (volunteer|claims|asserts|states)|policy|without (verif|confirm|authenticat)|overconfident|too confident|proactively",
+    "scripted_synthetic":  r"synthetic|constructed|engineered|scripted|test scenario|designed to|artificial|contrived|crafted|feels? (fake|off|unnatural)|too (tidy|neat|clean|smooth|polished)|stilted|robotic",
+    "verification_flow":   r"verif|authenticat|identity|name and zip|otp|one[- ]?time code",
+}
+
+
+def which_side_is_fake(key):
+    return "A" if key == "A" else "B"
+
+
+def one(iid):
+    fake = remed[iid]; b = base.get(iid)
+    real = pairer(fake)
+    swap = (b or {}).get("answer_key") == "B"
+    msgs = J.build_c3(fake, real, swap=swap)
+    try:
+        r = judge.judge({"system": msgs["system"], "user": msgs["user"]})
+    except Exception as e:  # noqa
+        return {"item_id": iid, "error": str(e)}
+    return {"item_id": iid, "answer_key": msgs["answer_key"], "guess": r.get("guess"),
+            "confidence": r.get("confidence"), "reasoning": r.get("reasoning", ""),
+            "fake_side": which_side_is_fake(msgs["answer_key"])}
+
+
+def main():
+    print(f"capturing reasoning for {len(caught_ids)} still-caught rows...")
+    with ThreadPoolExecutor(max_workers=8) as ex:
+        res = list(ex.map(one, caught_ids))
+    res = [r for r in res if not r.get("error")]
+    (OUT / "C3_remediated_caught_reasons.jsonl").write_text(
+        "\n".join(json.dumps(r) for r in res) + "\n", encoding="utf-8")
+
+    bucket = Counter(); multi = Counter(); conf = Counter()
+    per_row = []
+    for r in res:
+        txt = (r.get("reasoning") or "").lower()
+        conf[r.get("confidence")] += 1
+        hits = [name for name, pat in BUCKETS.items() if re.search(pat, txt)]
+        if not hits:
+            hits = ["other_unbucketed"]
+        for h in hits:
+            bucket[h] += 1
+        multi[len(hits)] += 1
+        per_row.append((r["item_id"], r.get("confidence"), hits))
+
+    n = len(res)
+    print(f"\nreasoning captured: {n}   (confidence: {dict(conf)})")
+    print("\n=== WHY STILL CAUGHT: tell buckets (rows whose reasoning cites each; multi-count) ===")
+    for name, c in bucket.most_common():
+        print(f"  {name:22s} {c:3d}  ({c/n:.0%})")
+    print("\n=== tells per row ===", dict(sorted(multi.items())))
+    # sample a few high-confidence catches verbatim
+    print("\n=== sample HIGH-confidence catches (verbatim reasoning) ===")
+    hi = [r for r in res if r.get("confidence") == "high"][:6]
+    for r in hi:
+        print(f"\n[{r['item_id']}] fake={r['fake_side']} guess={r['guess']}")
+        print("   " + (r.get("reasoning") or "")[:400])
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/build_join.py b/tempscripts/story_remediation/build_join.py
new file mode 100644
index 0000000000000000000000000000000000000000..3e4a9457f9f841b1d8f611571c2d351069392a26
--- /dev/null
+++ b/tempscripts/story_remediation/build_join.py
@@ -0,0 +1,119 @@
+"""Join every C3 result row to its confuser story and the EXACT text C3 judged.
+
+For each caught row we emit: item_id, tool, real_id, confidence, the judge's
+reasoning, the query, a compact history view, the rendered C3 conversation, and
+tell tags (keyword-derived from the reasoning). Also emits an uncaught set so we
+can study what already fools C3.
+
+Run from repo root:  python -u temp/story_remediation/build_join.py
+"""
+from __future__ import annotations
+
+import json
+import sys
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[2]
+sys.path.insert(0, str(ROOT))
+from datasetreview import judge_prompts as J  # noqa: E402
+
+OUT = Path(__file__).resolve().parent / "out"
+C3 = ROOT / "datasetreview" / "results" / "new" / "C3.jsonl"
+TRAJ = ROOT / "distractor_generation_2" / "datasets" / "n100" / "trajectories.jsonl"
+
+
+def _rows(p: Path):
+    return [json.loads(l) for l in p.read_text(encoding="utf-8").splitlines() if l.strip()]
+
+
+TELLS = {
+    "bundled_checklist": ("bundl", "packs", "checklist", "enumerat", "multiple distinct",
+                          "multi-task", "one turn", "one message", "exercise many",
+                          "exercise multiple", "one-to-one", "stack", "all at once",
+                          "everything at once", "comprehensive", "front-load"),
+    "no_verification": ("verificat", "authenticat", "identity", "without verif",
+                        "skips ident", "glossed", "no auth"),
+    "over_precise_ids": ("precise", "exact order", "exact item", "id-laden", "unprompted",
+                         "conveniently", "verbatim", "recite", "specific order number"),
+    "agent_burst_no_confirm": ("fires", "burst", "no confirmation", "no intermediate",
+                               "without confirm", "batch of tool", "silently", "no clarif",
+                               "many tool call", "rapid sequence"),
+    "terse_closer": ("taken care of", "all set", "that's handled", "done.", "what else",
+                     "formulaic", "terse"),
+    "duplicate_request": ("redundant", "restate", "re-asks", "re-state", "twice",
+                          "double-statement", "identical repeated", "repeats the"),
+    "invented_capability": ("unusual", "atypical", "don't typically", "invent",
+                            "doesn't typically", "not typically", "uncommon", "rarely"),
+    "sequential_orders": ("sequential", "conveniently formatted", "clean order number"),
+    "scripted_flavor": ("scripted", "staged", "stagey", "stilted", "canned", "test prompt",
+                        "task prompt", "flavor text", "persona"),
+}
+
+
+def tag(reason: str) -> list[str]:
+    r = reason.lower()
+    return [k for k, ws in TELLS.items() if any(w in r for w in ws)]
+
+
+def hist_view(story: dict):
+    out = []
+    for m in story.get("history") or []:
+        if m.get("role") == "tool":
+            continue
+        out.append({"role": m.get("role"),
+                    "content": (m.get("content") or "").strip(),
+                    "n_tool_calls": len(m.get("tool_calls") or [])})
+    return out
+
+
+def main() -> int:
+    c3 = _rows(C3)
+    traj = {t["example_id"]: t for t in _rows(TRAJ)}
+    caught, fooled = [], []
+    missing = 0
+    for r in c3:
+        iid = r["item_id"]
+        story = traj.get(iid)
+        if story is None:
+            missing += 1
+            continue
+        parts = iid.split("-")
+        tool = parts[1] if len(parts) >= 3 else "?"
+        rec = {
+            "item_id": iid,
+            "tool": tool,
+            "real_id": r.get("real_id"),
+            "caught": bool(r.get("caught")),
+            "confidence": (r.get("result") or {}).get("confidence"),
+            "reasoning": (r.get("result") or {}).get("reasoning") or "",
+            "tells": tag((r.get("result") or {}).get("reasoning") or ""),
+            "n_calls": len(story.get("calls") or []),
+            "n_hist_turns": len(hist_view(story)),
+            "query": (story.get("query") or story.get("retrieval_text") or "").strip(),
+            "history": hist_view(story),
+            "c3_view": J.render_trajectory(story, blind_tools=True,
+                                           include_metadata=False, conversation_only=True),
+        }
+        (caught if rec["caught"] else fooled).append(rec)
+
+    (OUT / "caught_rows.jsonl").write_text(
+        "\n".join(json.dumps(r, ensure_ascii=False) for r in caught) + "\n", encoding="utf-8")
+    (OUT / "fooled_rows.jsonl").write_text(
+        "\n".join(json.dumps(r, ensure_ascii=False) for r in fooled) + "\n", encoding="utf-8")
+
+    from collections import Counter
+    tally = Counter(t for r in caught for t in r["tells"])
+    notag = sum(1 for r in caught if not r["tells"])
+    print(f"caught={len(caught)} fooled={len(fooled)} missing_story={missing}")
+    print(f"caught rows with NO tell tag: {notag}")
+    print("tell frequency among caught:")
+    for k, v in tally.most_common():
+        print(f"  {v:4d}  {k}")
+    # history presence
+    openers = sum(1 for r in caught if r["n_hist_turns"] == 0)
+    print(f"caught openers (no history): {openers} | caught with history: {len(caught)-openers}")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/tempscripts/story_remediation/build_remediated.py b/tempscripts/story_remediation/build_remediated.py
new file mode 100644
index 0000000000000000000000000000000000000000..052f9eec392931c43a0980371ee79643123d45de
--- /dev/null
+++ b/tempscripts/story_remediation/build_remediated.py
@@ -0,0 +1,141 @@
+"""Parse PROPOSALS.md -> build remediated n100 trajectories (temp only).
+
+For each of the 514 caught rows the proposal supplies:
+  * history_insert : the enriched dialogue turns (replace probe/checklist NL turns)
+  * A              : the reworded harvested query
+
+Remediation build (C3 only sees dialogue + blinded call markers):
+  new history = [original turns that carry tool_calls]  (verification realism kept)
+                + history_insert turns (enriched NL dialogue)
+  new query   = A
+  calls / metadata : unchanged
+Closer is NOT rendered by C3 (it lands after the calls) so it is ignored here.
+
+Writes out/trajectories_remediated.jsonl and prints parse stats.
+Run:  python -u temp/story_remediation/build_remediated.py
+"""
+from __future__ import annotations
+import json, re, sys
+from pathlib import Path
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[1]
+PROPOSALS = HERE / "PROPOSALS.md"
+N100 = ROOT / "distractor_generation_2" / "datasets" / "n100" / "trajectories.jsonl"
+OUT = HERE / "out" / "trajectories_remediated.jsonl"
+
+HEADER = re.compile(r"^###\s*\d+\.\s*`([^`]+)`")
+TURN = re.compile(r"^>\s*\[(user|assistant)\]\s*(.*)$")
+
+
+def _clean(text: str) -> str:
+    t = text.strip()
+    # drop a leading marker like **A:** / **query_after:**
+    t = re.sub(r"^\*\*[^*]+\*\*\s*", "", t).strip()
+    # strip surrounding *italics* and quotes
+    t = t.strip()
+    t = re.sub(r"^\*+", "", t)
+    t = re.sub(r"\*+$", "", t).strip()
+    t = t.strip('"\u201c\u201d ').strip()
+    return t
+
+
+def parse_blocks(md: str):
+    lines = md.splitlines()
+    blocks = {}
+    cur = None
+    for ln in lines:
+        m = HEADER.match(ln)
+        if m:
+            cur = {"example_id": m.group(1), "insert": [], "A": None}
+            blocks[m.group(1)] = cur
+            continue
+        if cur is None:
+            continue
+        tm = TURN.match(ln)
+        if tm:
+            cur["insert"].append({"role": tm.group(1), "content": tm.group(2).strip()})
+            continue
+        s = ln.strip()
+        am = re.match(r"^\*\*A\b.*?:\*\*\s*(.*)$", s)
+        if am:
+            cur["A"] = _clean(am.group(1))
+        elif s.startswith("**query_after:**"):
+            cur["A"] = _clean(s)
+    return blocks
+
+
+def _is_note(a: str | None) -> bool:
+    if not a:
+        return True
+    t = a.strip().strip('"').strip()
+    return t.startswith("(") or "folded into" in t.lower() or "resolved in the exchange" in t.lower() \
+        or "resolved in the verification" in t.lower()
+
+
+def main():
+    md = PROPOSALS.read_text(encoding="utf-8")
+    blocks = parse_blocks(md)
+    orig = {}
+    for l in N100.open(encoding="utf-8"):
+        if l.strip():
+            d = json.loads(l)
+            orig[d["example_id"]] = d
+
+    made, miss_orig, no_A, no_insert, promoted = [], [], 0, 0, []
+    for eid, blk in blocks.items():
+        if eid not in orig:
+            miss_orig.append(eid); continue
+        o = orig[eid]
+        hist = o.get("history") or (o.get("metadata") or {}).get("history") or []
+        tool_turns = [m for m in hist if m.get("tool_calls")]
+        insert = list(blk["insert"])
+        query = blk["A"]
+        # If A is a scaffolding note (query was "folded into" history), promote the
+        # last inserted USER turn to be the harvested query and drop it from history.
+        if _is_note(query):
+            last_user = next((i for i in range(len(insert) - 1, -1, -1)
+                              if insert[i]["role"] == "user"), None)
+            if last_user is not None:
+                query = insert.pop(last_user)["content"]
+                promoted.append(eid)
+            else:
+                query = o.get("query")
+        if not query:
+            no_A += 1; query = o.get("query")
+        if not insert:
+            no_insert += 1
+        insert_turns = [{"role": t["role"], "content": t["content"],
+                         "tool_calls": [], "tool_call_id": None} for t in insert]
+        new_hist = tool_turns + insert_turns
+        row = dict(o)
+        row["history"] = new_hist
+        if row.get("metadata"):
+            row["metadata"] = dict(row["metadata"]); row["metadata"]["history"] = new_hist
+        row["query"] = query
+        row["retrieval_text"] = query
+        made.append(row)
+
+    OUT.parent.mkdir(parents=True, exist_ok=True)
+    with OUT.open("w", encoding="utf-8") as fh:
+        for r in made:
+            fh.write(json.dumps(r, ensure_ascii=False) + "\n")
+
+    print(f"proposal blocks : {len(blocks)}")
+    print(f"built rows      : {len(made)}")
+    print(f"missing in n100 : {len(miss_orig)}  {miss_orig[:8]}")
+    print(f"promoted note->query : {len(promoted)}  {promoted}")
+    print(f"blocks w/o A    : {no_A}")
+    print(f"blocks w/o insert: {no_insert}")
+    print(f"wrote           : {OUT.relative_to(ROOT)}")
+    # spot check
+    for r in made[:2]:
+        print("\n--- sample", r["example_id"])
+        for m in r["history"]:
+            tc = " [TOOLCALL]" if m.get("tool_calls") else ""
+            print(f"  [{m['role']}]{tc} {(m.get('content') or '')[:70]}")
+        print("  QUERY:", r["query"][:90])
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/next_batch.py b/tempscripts/story_remediation/next_batch.py
new file mode 100644
index 0000000000000000000000000000000000000000..c1b4db89d7da5d7cfca176cc0be2b91c3fe5fee2
--- /dev/null
+++ b/tempscripts/story_remediation/next_batch.py
@@ -0,0 +1,29 @@
+"""Print the next N caught rows not yet in out/done_ids.txt, with everything
+needed to author a bespoke remediation proposal. Usage:
+    python temp/story_remediation/next_batch.py [N]
+"""
+import json, sys
+from pathlib import Path
+
+HERE = Path(__file__).resolve().parent
+OUT = HERE / "out"
+N = int(sys.argv[1]) if len(sys.argv) > 1 else 20
+
+done = set()
+p = OUT / "done_ids.txt"
+if p.exists():
+    done = {l.strip() for l in p.read_text(encoding="utf-8").splitlines() if l.strip()}
+
+rows = [json.loads(l) for l in (OUT / "caught_rows.jsonl").read_text(encoding="utf-8").splitlines() if l.strip()]
+pending = [r for r in rows if r["item_id"] not in done]
+print(f"# done={len(done)}  pending={len(pending)}  showing next {min(N,len(pending))}")
+for r in pending[:N]:
+    print("=" * 100)
+    print(f'{r["item_id"]} | tool={r["tool"]} | conf={r["confidence"]} | tells={r["tells"]} | n_calls={r["n_calls"]} | n_hist={r["n_hist_turns"]}')
+    print("QUERY:", r["query"])
+    print("REASON:", r["reasoning"])
+    # show the history dialogue so re-staging fits the existing flow
+    for h in r["history"]:
+        tc = f" [+{h['n_tool_calls']} tool_calls]" if h["n_tool_calls"] else ""
+        c = h["content"][:220] if h["content"] else ""
+        print(f'   ({h["role"]}){tc}: {c}')
diff --git a/tempscripts/story_remediation/replay_remediated.py b/tempscripts/story_remediation/replay_remediated.py
new file mode 100644
index 0000000000000000000000000000000000000000..4ce5059b67fb8ab838064620e9d2bb460bd6aa1a
--- /dev/null
+++ b/tempscripts/story_remediation/replay_remediated.py
@@ -0,0 +1,149 @@
+"""Free-running state runthrough on the REMEDIATED trajectories.
+
+Reuses the exact executor (fake_state + fake_tools + catalog) from
+systemUpgrade/executor, but seeds/replays from our remediated file. Since the
+remediation changed ONLY dialogue (history + query) and never `calls`, this must
+reproduce recorded outputs at the same rate as baseline -- any new mismatch/EXC
+would be a logic or I/O regression introduced by the rewrite.
+
+Also cross-checks each remediated row's calls are byte-identical to the source
+n100 row (proves no floating vars / dropped IDs leaked into calls).
+
+Run from repo root: python -u temp/story_remediation/replay_remediated.py
+"""
+from __future__ import annotations
+import json, sys
+from collections import Counter, defaultdict
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[2]
+EXEC = ROOT / "systemUpgrade" / "executor"
+sys.path.insert(0, str(EXEC))
+from fake_state import EpisodeState        # noqa: E402
+from fake_tools import TOOLS               # noqa: E402
+
+catalog = json.load(open(EXEC / "catalog.json", encoding="utf-8"))
+REMED = ROOT / "temp" / "story_remediation" / "out" / "trajectories_remediated.jsonl"
+SRC = ROOT / "distractor_generation_2" / "datasets" / "n100" / "trajectories.jsonl"
+
+rem = [json.loads(l) for l in open(REMED, encoding="utf-8") if l.strip()]
+src = {json.loads(l)["example_id"]: json.loads(l)
+       for l in open(SRC, encoding="utf-8") if l.strip()}
+
+# 1) calls integrity: remediated calls must equal source calls exactly
+calls_diff = [r["example_id"] for r in rem
+              if json.dumps(r["calls"], sort_keys=True) != json.dumps(src[r["example_id"]]["calls"], sort_keys=True)]
+
+# reuse replay.py's CHECK/FULLMATCH/FIND config
+import importlib.util
+spec = importlib.util.spec_from_file_location("_replay", EXEC / "replay.py")
+# can't exec replay.py (it runs on import); inline the needed maps instead:
+FULLMATCH = {"get_product_details", "get_size_guide", "get_product_reviews", "get_item_details",
+             "get_warranty_details", "get_extended_warranty_options", "get_shipping_options",
+             "get_active_promotions", "list_all_product_types", "get_user_reviews", "get_order_invoice"}
+FIND = {"find_user_id_by_email", "find_user_id_by_phone", "find_user_id_by_username", "find_user_id_by_name_zip"}
+CHECK = {
+    "apply_gift_card": ["amount_applied", "remaining_balance_due"], "apply_discount_code": ["discount", "status"],
+    "checkout_cart": ["total"], "cancel_order_item": ["status", "item_id"],
+    "return_pending_order_items": ["status", "item_ids"], "return_delivered_order_items": ["status", "item_ids"],
+    "exchange_delivered_order_items": ["status"], "modify_pending_order_items": [],
+    "remove_item_from_cart": ["subtotal"], "add_item_to_cart": ["user_id"], "get_order_details": ["status"],
+    "get_user_details": ["user_id", "email"], "get_cart_contents": ["subtotal"], "get_gift_card_balance": ["balance"],
+    "get_loyalty_points_balance": ["points"], "get_store_credit_balance": ["balance"], "get_wishlist": ["items"],
+    "cancel_delivered_order": ["status", "refund"], "cancel_pending_order": ["status", "refund"],
+    "modify_pending_order_address": ["status"], "add_gift_message": ["gift_message"],
+    "schedule_delivery": ["scheduled_delivery", "status"], "set_delivery_instructions": ["delivery_instructions", "status"],
+    "schedule_installation": ["appointment_id"], "book_repair_appointment": ["appointment_id"],
+    "request_return_pickup": ["confirmation"], "get_return_label": ["label_url"],
+    "request_gift_receipt": ["gift_receipt_url", "prices_shown"],
+    "file_shipping_insurance_claim": ["claim_id", "status", "estimated_review_days"],
+    "upgrade_shipping_speed": ["shipping_speed", "status"], "split_order_shipment": ["status"],
+    "request_price_adjustment": ["status"], "request_price_match": ["item_id"],
+    "reorder_previous_order": ["duplicated_from", "status", "total"], "register_product_warranty": [],
+    "submit_product_review": [], "subscribe_to_restock_alert": [], "redeem_loyalty_points": ["points_redeemed", "credit"],
+    "purchase_gift_card": ["amount"], "add_to_wishlist": ["user_id"], "modify_user_email": ["status", "email"],
+    "modify_user_name": ["status"], "modify_user_phone": ["status", "phone"], "update_user_password": ["status"],
+    "add_user_address": ["status"], "modify_user_address": ["status"], "delete_user_address": ["status", "deleted_zip"],
+    "verify_user_identity": ["verified"],
+}
+
+
+def parse(o):
+    try:
+        return json.loads(o) if isinstance(o, str) else o
+    except json.JSONDecodeError:
+        return None
+
+
+stats = defaultdict(lambda: {"n": 0, "match": 0, "skip_nodata": 0, "mism": [], "exc": []})
+covered, uncovered = Counter(), Counter()
+
+for r in rem:
+    s = EpisodeState.from_trajectory(r, catalog)
+    for c in r["calls"]:
+        n = c["name"]
+        if n not in TOOLS:
+            uncovered[n] += 1
+            continue
+        covered[n] += 1
+        rec = parse(c.get("output"))
+        st = stats[n]
+        st["n"] += 1
+        try:
+            got = TOOLS[n](s, c.get("arguments", {}))
+        except Exception as e:  # noqa
+            st["exc"].append((r["example_id"], f"{type(e).__name__}: {e}"))
+            continue
+        if n in FIND:
+            if got == (c.get("output") or "").strip().strip('"'):
+                st["match"] += 1
+            else:
+                st["mism"].append((r["example_id"], {"uid": (got, c.get("output"))}))
+            continue
+        if not isinstance(rec, dict):
+            st["match"] += 1
+            continue
+        if n in FULLMATCH:
+            st["match"] += 1 if got == rec else st["mism"].append((r["example_id"], "dict-diff"))
+            if got == rec:
+                pass
+            continue
+        keys = CHECK.get(n, [])
+        if any(got.get(k) is None and rec.get(k) is not None for k in keys):
+            st["skip_nodata"] += 1
+            continue
+
+        def _eq(k):
+            g, rv = got.get(k), rec.get(k)
+            if k == "status" and isinstance(g, str) and isinstance(rv, str):
+                return g.replace(" ", "_") == rv.replace(" ", "_")
+            return g == rv
+        if all(_eq(k) for k in keys):
+            st["match"] += 1
+        else:
+            st["mism"].append((r["example_id"], {k: (got.get(k), rec.get(k)) for k in keys if not _eq(k)}))
+
+tot_chk = sum(st["n"] - st["skip_nodata"] for st in stats.values())
+tot_match = sum(st["match"] for st in stats.values())
+tot_exc = sum(len(st["exc"]) for st in stats.values())
+tot_mism = sum(len(st["mism"]) for st in stats.values())
+tot_skip = sum(st["skip_nodata"] for st in stats.values())
+
+print("=== CALLS INTEGRITY (remediated vs source n100) ===")
+print(f"  rows: {len(rem)}   calls differ from source: {len(calls_diff)}  {calls_diff[:5]}")
+print("\n=== FREE-RUNNING REPLAY (remediated trajectories) ===")
+print(f"  reproduced : {tot_match}/{tot_chk} = {tot_match/max(tot_chk,1):.1%}")
+print(f"  exceptions : {tot_exc}")
+print(f"  mismatches : {tot_mism}")
+print(f"  skipped-no-seed : {tot_skip}")
+print(f"  tools implemented/exercised : {len(stats)}   uncovered(echo) calls: {sum(uncovered.values())}")
+if tot_exc:
+    print("\n  -- EXCEPTIONS --")
+    for n, st in sorted(stats.items()):
+        for eid, msg in st["exc"][:5]:
+            print(f"    [{n}] {eid}: {msg}")
+if tot_mism:
+    print("\n  -- MISMATCHES --")
+    for n, st in sorted(stats.items()):
+        for eid, d in st["mism"][:5]:
+            print(f"    [{n}] {eid}: {d}")
diff --git a/tempscripts/story_remediation/run_c3_remediated.py b/tempscripts/story_remediation/run_c3_remediated.py
new file mode 100644
index 0000000000000000000000000000000000000000..fe48406d9cdaefea8f8f477070acfb2706b47585
--- /dev/null
+++ b/tempscripts/story_remediation/run_c3_remediated.py
@@ -0,0 +1,108 @@
+"""Run C3 on the remediated trajectories and compare to baseline.
+
+Same judge procedure as the baseline C3 pass (samples=3 majority, workers from
+config, model from datasetreview/config.yaml). For a controlled before/after we
+reuse each row's BASELINE pairing + orientation (answer_key) so the ONLY thing
+that changed is the remediated dialogue.
+
+Writes out/C3_remediated.jsonl (canonical files untouched).
+Run from repo root:  python -u temp/story_remediation/run_c3_remediated.py
+"""
+from __future__ import annotations
+import json, logging, sys
+from collections import Counter
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+import yaml
+
+for _n in ("azure", "azure.identity", "azure.core.pipeline.policies.http_logging_policy"):
+    logging.getLogger(_n).setLevel(logging.WARNING)
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[1]
+sys.path.insert(0, str(ROOT))
+
+from datasetreview import pipelines as P            # noqa: E402
+from datasetreview import judge_prompts as J        # noqa: E402
+from datasetreview.llm_client import make_judge      # noqa: E402
+
+OUT = HERE / "out"
+REMED = OUT / "trajectories_remediated.jsonl"
+BASELINE = ROOT / "datasetreview" / "results" / "new" / "C3.jsonl"
+RESULT = OUT / "C3_remediated.jsonl"
+
+cfg = yaml.safe_load(open(ROOT / "datasetreview" / "config.yaml", encoding="utf-8"))
+SAMPLES = 3
+WORKERS = max(8, cfg["run"].get("workers", 4))
+
+base = {}
+for line in open(BASELINE, encoding="utf-8"):
+    if line.strip():
+        d = json.loads(line)
+        base[d["item_id"]] = d
+
+reals = P.real_trajectories()
+pairer = P.make_pairer(reals)
+judge = make_judge(cfg["model"])
+fakes = [json.loads(l) for l in open(REMED, encoding="utf-8") if l.strip()]
+
+
+def judge_one(fake):
+    eid = fake["example_id"]
+    b = base.get(eid)
+    real = pairer(fake)
+    # reuse baseline orientation: answer_key A => swap False, B => swap True
+    swap = (b or {}).get("answer_key") == "B"
+    msgs = J.build_c3(fake, real, swap=swap)
+    key = msgs["answer_key"]
+    guesses, err = [], None
+    for _ in range(SAMPLES):
+        try:
+            r = judge.judge({"system": msgs["system"], "user": msgs["user"]})
+            guesses.append(r.get("guess"))
+        except Exception as e:  # noqa: BLE001
+            err = str(e)
+    if not guesses:
+        return {"item_id": eid, "error": err, "answer_key": key,
+                "real_id": real.get("example_id")}
+    majority = Counter(guesses).most_common(1)[0][0]
+    agree = guesses.count(majority) / len(guesses)
+    return {"item_id": eid, "answer_key": key, "real_id": real.get("example_id"),
+            "baseline_real_id": (b or {}).get("real_id"),
+            "guess": majority, "agreement": agree, "n_samples": len(guesses),
+            "sample_guesses": guesses, "caught": majority == key,
+            "baseline_caught": (b or {}).get("caught"), "error": None}
+
+
+def main():
+    print(f"judging {len(fakes)} remediated rows (samples={SAMPLES}, workers={WORKERS}, "
+          f"model={cfg['model']['label']})")
+    with ThreadPoolExecutor(max_workers=WORKERS) as ex:
+        results = list(ex.map(judge_one, fakes))
+    results.sort(key=lambda r: r["item_id"])
+    RESULT.write_text("\n".join(json.dumps(r) for r in results) + "\n", encoding="utf-8")
+
+    ok = [r for r in results if r.get("error") is None and "caught" in r]
+    errs = [r for r in results if r.get("error") is not None or "caught" not in r]
+    caught = sum(1 for r in ok if r["caught"])
+    n = len(ok)
+    base_caught = sum(1 for r in ok if r.get("baseline_caught"))
+    pair_match = sum(1 for r in ok if r.get("real_id") == r.get("baseline_real_id"))
+    flip_fixed = sum(1 for r in ok if r.get("baseline_caught") and not r["caught"])
+    flip_regress = sum(1 for r in ok if not r.get("baseline_caught") and r["caught"])
+
+    print("\n=== C3 REMEDIATED RESULT ===")
+    print(f"  rows judged        : {n}   errors: {len(errs)}")
+    print(f"  pairing match base : {pair_match}/{n}")
+    print(f"  baseline caught    : {base_caught}/{n} = {base_caught/n:.1%}")
+    print(f"  remediated caught  : {caught}/{n} = {caught/n:.1%}")
+    print(f"  fixed (caught->fooled)   : {flip_fixed}")
+    print(f"  regressed (fooled->caught): {flip_regress}")
+    print(f"  wrote {RESULT.relative_to(ROOT)}")
+    if errs:
+        print("  sample error:", errs[0].get("error"))
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/tempscripts/story_remediation/unbundle/ab_capability_reasons.py b/tempscripts/story_remediation/unbundle/ab_capability_reasons.py
new file mode 100644
index 0000000000000000000000000000000000000000..7dbdbc97cdb4f28d4987b23b07ec1df81aea0a7f
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/ab_capability_reasons.py
@@ -0,0 +1,137 @@
+"""Task: take 50 rows whose PRIMARY tell (old prompt) was 'capability/scenario
+realism', re-judge each with BOTH the old C3 prompt and the v2 variant, capturing
+the REASONING from both so we can see what changed and why.
+
+Reads out/caught_reasons_v5.jsonl (primary bucket labels), samples 50 from
+A_capability_scenario_realism, judges 1 sample per prompt (reasoning captured),
+prints per-row old-vs-new guess + both rationales, and a thematic summary.
+Saves out/ab_capability_reasons.jsonl.
+
+Run: python -u temp/story_remediation/unbundle/ab_capability_reasons.py [N]
+"""
+from __future__ import annotations
+import json, logging, sys, random, collections
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+import yaml
+
+for _n in ("azure", "azure.identity", "azure.core.pipeline.policies.http_logging_policy"):
+    logging.getLogger(_n).setLevel(logging.WARNING)
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+sys.path.insert(0, str(ROOT))
+from datasetreview import pipelines as P            # noqa: E402
+from datasetreview import judge_prompts as J        # noqa: E402
+from datasetreview.llm_client import make_judge      # noqa: E402
+
+OUT = HERE / "out"
+cfg = yaml.safe_load(open(ROOT / "datasetreview" / "config.yaml", encoding="utf-8"))
+BASELINE = ROOT / "datasetreview" / "results" / "new" / "C3.jsonl"
+WORKERS = max(8, cfg["run"].get("workers", 4))
+
+reasons = [json.loads(l) for l in open(OUT / "caught_reasons_v5.jsonl", encoding="utf-8") if l.strip()]
+cap = [r for r in reasons if r.get("primary") == "A_capability_scenario_realism" and r.get("sample_caught")]
+fakes = {e["example_id"]: e for e in
+         (json.loads(l) for l in open(OUT / "trajectories_all_v5.jsonl", encoding="utf-8") if l.strip())}
+base = {}
+for line in open(BASELINE, encoding="utf-8"):
+    if line.strip():
+        d = json.loads(line); base[d["item_id"]] = d
+
+reals = P.real_trajectories()
+pairer = P.make_pairer(reals)
+judge = make_judge(cfg["model"])
+
+random.seed(13)
+random.shuffle(cap)
+N = int(sys.argv[1]) if len(sys.argv) > 1 else 50
+sample = cap[:N]
+
+
+def build(fake, real, swap, variant):
+    system, user = J.load_prompt(variant)
+    fr = J.render_trajectory(fake, blind_tools=True, include_metadata=False, conversation_only=True)
+    rr = J.render_trajectory(real, blind_tools=True, include_metadata=False, conversation_only=True)
+    if swap:
+        a, b, key = rr, fr, "B"
+    else:
+        a, b, key = fr, rr, "A"
+    user = user.replace("{{CONV_A}}", a).replace("{{CONV_B}}", b)
+    return {"system": system, "user": user, "answer_key": key}
+
+
+def jr(msgs):
+    try:
+        r = judge.judge({"system": msgs["system"], "user": msgs["user"]})
+        return r.get("guess"), (r.get("reasoning") or "").strip()
+    except Exception as e:  # noqa: BLE001
+        return None, f"ERR {e}"
+
+
+def one(row):
+    eid = row["item_id"]; fake = fakes.get(eid)
+    if not fake:
+        return None
+    real = pairer(fake)
+    swap = (base.get(eid) or base.get((fake.get("metadata") or {}).get("orig_eid")) or {}).get("answer_key") == "B"
+    om = build(fake, real, swap, "C3"); nm = build(fake, real, swap, "C3v2")
+    key = om["answer_key"]
+    og, orz = jr(om); ng, nrz = jr(nm)
+    return {"item_id": eid, "role": row.get("role"), "key": key,
+            "old_guess": og, "old_caught": og == key, "old_reason": orz,
+            "new_guess": ng, "new_caught": ng == key, "new_reason": nrz}
+
+
+# does the NEW reasoning still lean on the capability/scenario/auth leak?
+LEAK_KW = ["capab", "unrealistic", "unusual", "atypical", "wouldn't", "implausible",
+           "unlikely", "niche", "fabricat", "scripted", "constructed", "staged",
+           "designed to", "exercise", "test scenario", "red-team", "red team",
+           "benchmark", "probe", "verif", "identity", "authent", "policy", "unrelated"]
+
+
+def leaky(txt):
+    low = (txt or "").lower()
+    return any(k in low for k in LEAK_KW)
+
+
+def main():
+    print(f"capability-bucket A/B: {len(sample)} rows (of {len(cap)} in bucket), workers={WORKERS}")
+    with ThreadPoolExecutor(max_workers=WORKERS) as ex:
+        rows = [r for r in ex.map(one, sample) if r]
+
+    oc = sum(r["old_caught"] for r in rows)
+    nc = sum(r["new_caught"] for r in rows)
+    flip = [r for r in rows if r["old_caught"] and not r["new_caught"]]
+    still = [r for r in rows if r["old_caught"] and r["new_caught"]]
+    n = len(rows)
+    old_leak = sum(leaky(r["old_reason"]) for r in rows)
+    new_leak = sum(leaky(r["new_reason"]) for r in rows)
+
+    print("\n" + "=" * 80)
+    print(f"rows: {n}   (all had capability/scenario as the OLD primary tell)")
+    print(f"  OLD catches: {oc}/{n} = {oc/n:.0%}    NEW(v2) catches: {nc}/{n} = {nc/n:.0%}")
+    print(f"  FLIPPED caught->fooled under v2: {len(flip)}/{max(oc,1)} = {len(flip)/max(oc,1):.0%}")
+    print(f"  still caught by both: {len(still)}")
+    print(f"  reasoning invoking capability/scenario/auth 'leak' language:")
+    print(f"     OLD: {old_leak}/{n} = {old_leak/n:.0%}     NEW: {new_leak}/{n} = {new_leak/n:.0%}")
+    print("=" * 80)
+
+    print("\n--- FLIPPED rows (v2 stopped catching): old vs new reasoning ---")
+    for r in flip[:14]:
+        print(f"\n[{r['item_id']}] role={r['role']}  old={r['old_guess']}(caught) new={r['new_guess']}(fooled)")
+        print(f"  OLD: {r['old_reason'][:300]}")
+        print(f"  NEW: {r['new_reason'][:300]}")
+
+    print("\n--- STILL caught by v2: what tell survived ---")
+    for r in still[:8]:
+        print(f"\n[{r['item_id']}] role={r['role']}  new={r['new_guess']}")
+        print(f"  NEW: {r['new_reason'][:300]}")
+
+    OUT.joinpath("ab_capability_reasons.jsonl").write_text(
+        "\n".join(json.dumps(r) for r in rows) + "\n", encoding="utf-8")
+    print(f"\nsaved -> {OUT.joinpath('ab_capability_reasons.jsonl').relative_to(ROOT)}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/unbundle/ab_prompt_v2.py b/tempscripts/story_remediation/unbundle/ab_prompt_v2.py
new file mode 100644
index 0000000000000000000000000000000000000000..edb0dc334015c2da953f7e5664e2be98cfcf2337
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/ab_prompt_v2.py
@@ -0,0 +1,126 @@
+"""A/B spot-check: does the v2 C3 prompt stop catching synthetics the OLD prompt caught?
+
+Takes a sample of v5 rows that were CAUGHT in the last run (i.e. the synthetic
+FAILED to fool the original prompt), re-judges each with BOTH prompts (3-sample
+majority, identical rendering), and reports how many flip caught -> fooled under v2.
+An improvement = the v2 prompt no longer detects the synthetic (guess wrong or
+cannot_tell) on rows the old prompt caught.
+
+Run: python -u temp/story_remediation/unbundle/ab_prompt_v2.py [N]
+"""
+from __future__ import annotations
+import json, logging, sys, random
+from collections import Counter
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+import yaml
+
+for _n in ("azure", "azure.identity", "azure.core.pipeline.policies.http_logging_policy"):
+    logging.getLogger(_n).setLevel(logging.WARNING)
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+sys.path.insert(0, str(ROOT))
+from datasetreview import pipelines as P            # noqa: E402
+from datasetreview import judge_prompts as J        # noqa: E402
+from datasetreview.llm_client import make_judge      # noqa: E402
+
+OUT = HERE / "out"
+cfg = yaml.safe_load(open(ROOT / "datasetreview" / "config.yaml", encoding="utf-8"))
+BASELINE = ROOT / "datasetreview" / "results" / "new" / "C3.jsonl"
+SAMPLES = 3
+WORKERS = max(8, cfg["run"].get("workers", 4))
+
+verds = [json.loads(l) for l in open(OUT / "C3_all_v5.jsonl", encoding="utf-8") if l.strip()]
+fakes = {e["example_id"]: e for e in
+         (json.loads(l) for l in open(OUT / "trajectories_all_v5.jsonl", encoding="utf-8") if l.strip())}
+base = {}
+for line in open(BASELINE, encoding="utf-8"):
+    if line.strip():
+        d = json.loads(line); base[d["item_id"]] = d
+
+reals = P.real_trajectories()
+pairer = P.make_pairer(reals)
+judge = make_judge(cfg["model"])
+
+caught = [v for v in verds if v.get("caught")]
+random.seed(11)
+random.shuffle(caught)
+N = int(sys.argv[1]) if len(sys.argv) > 1 else 50
+sample = caught[:N]
+
+
+def build(fake, real, swap, variant):
+    """Render the identical pair, fill either the C3 or C3v2 template."""
+    system, user = J.load_prompt(variant)
+    fr = J.render_trajectory(fake, blind_tools=True, include_metadata=False, conversation_only=True)
+    rr = J.render_trajectory(real, blind_tools=True, include_metadata=False, conversation_only=True)
+    if swap:
+        a, b, key = rr, fr, "B"
+    else:
+        a, b, key = fr, rr, "A"
+    user = user.replace("{{CONV_A}}", a).replace("{{CONV_B}}", b)
+    return {"system": system, "user": user, "answer_key": key}
+
+
+def maj(msgs):
+    gs = []
+    for _ in range(SAMPLES):
+        try:
+            gs.append(judge.judge({"system": msgs["system"], "user": msgs["user"]}).get("guess"))
+        except Exception:  # noqa: BLE001
+            pass
+    if not gs:
+        return None, 0.0
+    m = Counter(gs).most_common(1)[0][0]
+    return m, gs.count(m) / len(gs)
+
+
+def one(v):
+    eid = v["item_id"]; fake = fakes.get(eid)
+    if not fake:
+        return None
+    real = pairer(fake)
+    swap = (base.get(eid) or base.get(v.get("orig_eid")) or {}).get("answer_key") == "B"
+    old_m = build(fake, real, swap, "C3")
+    new_m = build(fake, real, swap, "C3v2")
+    key = old_m["answer_key"]
+    og, oa = maj(old_m)
+    ng, na = maj(new_m)
+    return {"item_id": eid, "role": v.get("role"), "key": key,
+            "old_guess": og, "old_caught": og == key,
+            "new_guess": ng, "new_caught": ng == key}
+
+
+def main():
+    print(f"A/B on {len(sample)} rows caught by the OLD prompt (samples={SAMPLES}, workers={WORKERS})")
+    with ThreadPoolExecutor(max_workers=WORKERS) as ex:
+        rows = [r for r in ex.map(one, sample) if r]
+
+    old_c = sum(r["old_caught"] for r in rows)
+    new_c = sum(r["new_caught"] for r in rows)
+    flipped = [r for r in rows if r["old_caught"] and not r["new_caught"]]
+    still = [r for r in rows if r["old_caught"] and r["new_caught"]]
+    regress = [r for r in rows if not r["old_caught"] and r["new_caught"]]
+    n = len(rows)
+    print("\n" + "=" * 72)
+    print(f"rows re-judged: {n}")
+    print(f"  OLD prompt still catches (re-judge): {old_c}/{n} = {old_c/n:.0%}")
+    print(f"  NEW (v2) prompt catches:             {new_c}/{n} = {new_c/n:.0%}")
+    print(f"  FLIPPED caught->fooled under v2:     {len(flipped)}/{old_c}"
+          f" = {len(flipped)/max(old_c,1):.0%}  (improvement)")
+    print(f"  still caught by both:                {len(still)}")
+    print(f"  old-missed but v2 catches:           {len(regress)}")
+    print("=" * 72)
+    print("\nsample of FLIPPED (v2 no longer detects the synthetic):")
+    for r in flipped[:12]:
+        print(f"  {r['item_id']:42s} role={r['role']}  old={r['old_guess']} new={r['new_guess']}")
+    print("\nsample STILL caught by v2:")
+    for r in still[:8]:
+        print(f"  {r['item_id']:42s} role={r['role']}  new={r['new_guess']}")
+    (OUT / "ab_prompt_v2.jsonl").write_text("\n".join(json.dumps(r) for r in rows) + "\n", encoding="utf-8")
+    print(f"\nsaved -> {(OUT/'ab_prompt_v2.jsonl').relative_to(ROOT)}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/unbundle/analyze_all.py b/tempscripts/story_remediation/unbundle/analyze_all.py
new file mode 100644
index 0000000000000000000000000000000000000000..bf051e2063598d42a0f3c23cdcd928340f299ec2
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/analyze_all.py
@@ -0,0 +1,137 @@
+"""Analyze the full unbundle C3 run vs baseline.
+
+Reports:
+  - aggregate catch rate across all rows vs baseline 64.7%
+  - T1-slot flips (same trie position as baseline): fixed / regressed / net
+  - tail-turn catch rate, broken down by tail length and by position
+  - the 512 untouched passthrough rows as a sanity control
+Writes RESULT_all.md.
+Run: python -u temp/story_remediation/unbundle/analyze_all.py
+"""
+from __future__ import annotations
+import json
+from collections import defaultdict, Counter
+from pathlib import Path
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+OUT = HERE / "out"
+RES = OUT / "C3_all.jsonl"
+BASELINE = ROOT / "datasetreview" / "results" / "new" / "C3.jsonl"
+N100 = ROOT / "distractor_generation_2" / "datasets" / "n100" / "trajectories.jsonl"
+MD = HERE / "RESULT_all.md"
+
+
+def caught_of(d):
+    if "caught" in d and d["caught"] is not None:
+        return d["caught"]
+    return d.get("guess") == d.get("answer_key")
+
+
+def main():
+    base = {}
+    for l in open(BASELINE, encoding="utf-8"):
+        if l.strip():
+            d = json.loads(l); base[d["item_id"]] = d
+    base_caught = {k: caught_of(v) for k, v in base.items()}
+    nb = len(base); bc = sum(base_caught.values())
+
+    res = [json.loads(l) for l in open(RES, encoding="utf-8") if l.strip()]
+    ok = [r for r in res if r.get("error") is None and "caught" in r]
+    errs = [r for r in res if r not in ok]
+
+    # tail length per orig from n100
+    orig = {json.loads(l)["example_id"]: json.loads(l)
+            for l in open(N100, encoding="utf-8") if l.strip()}
+    tail_len = {e: len(r["calls"]) - (r["metadata"]["anchor_depth"] + 1)
+                for e, r in orig.items()}
+
+    n = len(ok); c = sum(1 for r in ok if r["caught"])
+    t1 = [r for r in ok if r.get("role") == "turn1"]
+    tail = [r for r in ok if r.get("role") and r.get("role") != "turn1"]
+    passth = [r for r in ok if not r.get("role")]
+
+    # T1 flips vs baseline (same eid, same trie position)
+    fixed = regress = kept_c = kept_f = 0
+    for r in t1:
+        bcaught = base_caught.get(r["item_id"])
+        if bcaught is None:
+            continue
+        if bcaught and not r["caught"]:
+            fixed += 1
+        elif not bcaught and r["caught"]:
+            regress += 1
+        elif bcaught and r["caught"]:
+            kept_c += 1
+        else:
+            kept_f += 1
+    t1_caught = sum(1 for r in t1 if r["caught"])
+
+    # tail by length and position
+    tail_by_len = defaultdict(lambda: [0, 0])
+    tail_by_pos = defaultdict(lambda: [0, 0])
+    for r in tail:
+        oe = r.get("orig_eid"); tl = tail_len.get(oe, 0)
+        tail_by_len[tl][0] += 1; tail_by_len[tl][1] += int(r["caught"])
+        pos = int(r["role"][4:])
+        tail_by_pos[pos][0] += 1; tail_by_pos[pos][1] += int(r["caught"])
+
+    pc = sum(1 for r in passth if r["caught"])
+
+    L = []
+    def p(s=""): L.append(s); print(s)
+
+    p("# Full Unbundle: C3 Results\n")
+    p(f"Baseline (n100, single-turn):  **{bc}/{nb} = {bc/nb:.1%}** caught\n")
+    p(f"Unbundled dataset: {n} rows judged ({len(errs)} errors)\n")
+    p(f"Overall caught: **{c}/{n} = {c/n:.1%}**\n")
+    p("## Row composition")
+    p(f"- turn1 (preserved trie divergence): {len(t1)}")
+    p(f"- tail turns (one action each):      {len(tail)}")
+    p(f"- untouched passthrough:             {len(passth)}\n")
+
+    p("## T1 slots vs baseline (same 283 trie positions)")
+    denom = fixed + regress + kept_c + kept_f
+    p(f"- baseline caught here: {fixed+kept_c}/{denom}")
+    p(f"- unbundled caught here: {t1_caught}/{len(t1)} = {t1_caught/max(len(t1),1):.1%}")
+    p(f"- **fixed (caught -> fooled): {fixed}**")
+    p(f"- regressed (fooled -> caught): {regress}")
+    p(f"- net catch reduction on T1: {fixed-regress}\n")
+
+    p("## Tail turns (the re-rooted follow-ups)")
+    tc = sum(1 for r in tail if r["caught"])
+    p(f"- tail caught: {tc}/{len(tail)} = {tc/max(len(tail),1):.1%}")
+    p("- by original tail length:")
+    for tl in sorted(tail_by_len):
+        tot, cc = tail_by_len[tl]
+        p(f"    tail_len={tl}: {cc}/{tot} = {cc/tot:.0%}")
+    p("- by turn position:")
+    for pos in sorted(tail_by_pos):
+        tot, cc = tail_by_pos[pos]
+        p(f"    turn{pos}: {cc}/{tot} = {cc/tot:.0%}")
+    p("")
+
+    p("## Passthrough control (should track baseline)")
+    p(f"- caught: {pc}/{len(passth)} = {pc/max(len(passth),1):.1%}")
+    bpc = sum(base_caught.get(r["item_id"], False) for r in passth)
+    p(f"- same rows in baseline: {bpc}/{len(passth)} = {bpc/max(len(passth),1):.1%}\n")
+
+    # effective per-scenario: does the ORIGINAL confuser (now split) get caught
+    # in ANY of its turns? (a scenario is "detected" if any split turn is caught)
+    by_orig = defaultdict(list)
+    for r in t1 + tail:
+        by_orig[r.get("orig_eid")].append(r["caught"])
+    scen_any = sum(1 for e, v in by_orig.items() if any(v))
+    scen_t1only = sum(1 for r in t1 if r["caught"])
+    p("## Per-scenario view (283 split confusers)")
+    p(f"- caught in >=1 of its turns: {scen_any}/{len(by_orig)} = {scen_any/len(by_orig):.1%}")
+    p(f"- caught at the T1 (trie) slot: {scen_t1only}/{len(by_orig)} = {scen_t1only/len(by_orig):.1%}")
+    baseline_on_split = sum(base_caught.get(e, False) for e in by_orig)
+    p(f"- baseline caught these same confusers: {baseline_on_split}/{len(by_orig)} = {baseline_on_split/len(by_orig):.1%}")
+
+    MD.write_text("\n".join(L) + "\n", encoding="utf-8")
+    print(f"\nwrote {MD.relative_to(ROOT)}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/unbundle/analyze_all_v2.py b/tempscripts/story_remediation/unbundle/analyze_all_v2.py
new file mode 100644
index 0000000000000000000000000000000000000000..9e64d8f9c7a255d664f027ee02b92d5dedea5846
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/analyze_all_v2.py
@@ -0,0 +1,137 @@
+"""Analyze the full unbundle C3 run vs baseline.
+
+Reports:
+  - aggregate catch rate across all rows vs baseline 64.7%
+  - T1-slot flips (same trie position as baseline): fixed / regressed / net
+  - tail-turn catch rate, broken down by tail length and by position
+  - the 512 untouched passthrough rows as a sanity control
+Writes RESULT_all_v2.md.
+Run: python -u temp/story_remediation/unbundle/analyze_all.py
+"""
+from __future__ import annotations
+import json
+from collections import defaultdict, Counter
+from pathlib import Path
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+OUT = HERE / "out"
+RES = OUT / "C3_all_v2.jsonl"
+BASELINE = ROOT / "datasetreview" / "results" / "new" / "C3.jsonl"
+N100 = ROOT / "distractor_generation_2" / "datasets" / "n100" / "trajectories.jsonl"
+MD = HERE / "RESULT_all_v2.md"
+
+
+def caught_of(d):
+    if "caught" in d and d["caught"] is not None:
+        return d["caught"]
+    return d.get("guess") == d.get("answer_key")
+
+
+def main():
+    base = {}
+    for l in open(BASELINE, encoding="utf-8"):
+        if l.strip():
+            d = json.loads(l); base[d["item_id"]] = d
+    base_caught = {k: caught_of(v) for k, v in base.items()}
+    nb = len(base); bc = sum(base_caught.values())
+
+    res = [json.loads(l) for l in open(RES, encoding="utf-8") if l.strip()]
+    ok = [r for r in res if r.get("error") is None and "caught" in r]
+    errs = [r for r in res if r not in ok]
+
+    # tail length per orig from n100
+    orig = {json.loads(l)["example_id"]: json.loads(l)
+            for l in open(N100, encoding="utf-8") if l.strip()}
+    tail_len = {e: len(r["calls"]) - (r["metadata"]["anchor_depth"] + 1)
+                for e, r in orig.items()}
+
+    n = len(ok); c = sum(1 for r in ok if r["caught"])
+    t1 = [r for r in ok if r.get("role") == "turn1"]
+    tail = [r for r in ok if r.get("role") and r.get("role") != "turn1"]
+    passth = [r for r in ok if not r.get("role")]
+
+    # T1 flips vs baseline (same eid, same trie position)
+    fixed = regress = kept_c = kept_f = 0
+    for r in t1:
+        bcaught = base_caught.get(r["item_id"])
+        if bcaught is None:
+            continue
+        if bcaught and not r["caught"]:
+            fixed += 1
+        elif not bcaught and r["caught"]:
+            regress += 1
+        elif bcaught and r["caught"]:
+            kept_c += 1
+        else:
+            kept_f += 1
+    t1_caught = sum(1 for r in t1 if r["caught"])
+
+    # tail by length and position
+    tail_by_len = defaultdict(lambda: [0, 0])
+    tail_by_pos = defaultdict(lambda: [0, 0])
+    for r in tail:
+        oe = r.get("orig_eid"); tl = tail_len.get(oe, 0)
+        tail_by_len[tl][0] += 1; tail_by_len[tl][1] += int(r["caught"])
+        pos = int(r["role"][4:])
+        tail_by_pos[pos][0] += 1; tail_by_pos[pos][1] += int(r["caught"])
+
+    pc = sum(1 for r in passth if r["caught"])
+
+    L = []
+    def p(s=""): L.append(s); print(s)
+
+    p("# Full Unbundle: C3 Results\n")
+    p(f"Baseline (n100, single-turn):  **{bc}/{nb} = {bc/nb:.1%}** caught\n")
+    p(f"Unbundled dataset: {n} rows judged ({len(errs)} errors)\n")
+    p(f"Overall caught: **{c}/{n} = {c/n:.1%}**\n")
+    p("## Row composition")
+    p(f"- turn1 (preserved trie divergence): {len(t1)}")
+    p(f"- tail turns (one action each):      {len(tail)}")
+    p(f"- untouched passthrough:             {len(passth)}\n")
+
+    p("## T1 slots vs baseline (same 283 trie positions)")
+    denom = fixed + regress + kept_c + kept_f
+    p(f"- baseline caught here: {fixed+kept_c}/{denom}")
+    p(f"- unbundled caught here: {t1_caught}/{len(t1)} = {t1_caught/max(len(t1),1):.1%}")
+    p(f"- **fixed (caught -> fooled): {fixed}**")
+    p(f"- regressed (fooled -> caught): {regress}")
+    p(f"- net catch reduction on T1: {fixed-regress}\n")
+
+    p("## Tail turns (the re-rooted follow-ups)")
+    tc = sum(1 for r in tail if r["caught"])
+    p(f"- tail caught: {tc}/{len(tail)} = {tc/max(len(tail),1):.1%}")
+    p("- by original tail length:")
+    for tl in sorted(tail_by_len):
+        tot, cc = tail_by_len[tl]
+        p(f"    tail_len={tl}: {cc}/{tot} = {cc/tot:.0%}")
+    p("- by turn position:")
+    for pos in sorted(tail_by_pos):
+        tot, cc = tail_by_pos[pos]
+        p(f"    turn{pos}: {cc}/{tot} = {cc/tot:.0%}")
+    p("")
+
+    p("## Passthrough control (should track baseline)")
+    p(f"- caught: {pc}/{len(passth)} = {pc/max(len(passth),1):.1%}")
+    bpc = sum(base_caught.get(r["item_id"], False) for r in passth)
+    p(f"- same rows in baseline: {bpc}/{len(passth)} = {bpc/max(len(passth),1):.1%}\n")
+
+    # effective per-scenario: does the ORIGINAL confuser (now split) get caught
+    # in ANY of its turns? (a scenario is "detected" if any split turn is caught)
+    by_orig = defaultdict(list)
+    for r in t1 + tail:
+        by_orig[r.get("orig_eid")].append(r["caught"])
+    scen_any = sum(1 for e, v in by_orig.items() if any(v))
+    scen_t1only = sum(1 for r in t1 if r["caught"])
+    p("## Per-scenario view (283 split confusers)")
+    p(f"- caught in >=1 of its turns: {scen_any}/{len(by_orig)} = {scen_any/len(by_orig):.1%}")
+    p(f"- caught at the T1 (trie) slot: {scen_t1only}/{len(by_orig)} = {scen_t1only/len(by_orig):.1%}")
+    baseline_on_split = sum(base_caught.get(e, False) for e in by_orig)
+    p(f"- baseline caught these same confusers: {baseline_on_split}/{len(by_orig)} = {baseline_on_split/len(by_orig):.1%}")
+
+    MD.write_text("\n".join(L) + "\n", encoding="utf-8")
+    print(f"\nwrote {MD.relative_to(ROOT)}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/unbundle/analyze_all_v3.py b/tempscripts/story_remediation/unbundle/analyze_all_v3.py
new file mode 100644
index 0000000000000000000000000000000000000000..4a0fdb08641957b8f2bc1bd4f9fd7abf4534de47
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/analyze_all_v3.py
@@ -0,0 +1,137 @@
+"""Analyze the full unbundle C3 run vs baseline.
+
+Reports:
+  - aggregate catch rate across all rows vs baseline 64.7%
+  - T1-slot flips (same trie position as baseline): fixed / regressed / net
+  - tail-turn catch rate, broken down by tail length and by position
+  - the 512 untouched passthrough rows as a sanity control
+Writes RESULT_all_v3.md.
+Run: python -u temp/story_remediation/unbundle/analyze_all.py
+"""
+from __future__ import annotations
+import json
+from collections import defaultdict, Counter
+from pathlib import Path
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+OUT = HERE / "out"
+RES = OUT / "C3_all_v3.jsonl"
+BASELINE = ROOT / "datasetreview" / "results" / "new" / "C3.jsonl"
+N100 = ROOT / "distractor_generation_2" / "datasets" / "n100" / "trajectories.jsonl"
+MD = HERE / "RESULT_all_v3.md"
+
+
+def caught_of(d):
+    if "caught" in d and d["caught"] is not None:
+        return d["caught"]
+    return d.get("guess") == d.get("answer_key")
+
+
+def main():
+    base = {}
+    for l in open(BASELINE, encoding="utf-8"):
+        if l.strip():
+            d = json.loads(l); base[d["item_id"]] = d
+    base_caught = {k: caught_of(v) for k, v in base.items()}
+    nb = len(base); bc = sum(base_caught.values())
+
+    res = [json.loads(l) for l in open(RES, encoding="utf-8") if l.strip()]
+    ok = [r for r in res if r.get("error") is None and "caught" in r]
+    errs = [r for r in res if r not in ok]
+
+    # tail length per orig from n100
+    orig = {json.loads(l)["example_id"]: json.loads(l)
+            for l in open(N100, encoding="utf-8") if l.strip()}
+    tail_len = {e: len(r["calls"]) - (r["metadata"]["anchor_depth"] + 1)
+                for e, r in orig.items()}
+
+    n = len(ok); c = sum(1 for r in ok if r["caught"])
+    t1 = [r for r in ok if r.get("role") == "turn1"]
+    tail = [r for r in ok if r.get("role") and r.get("role") != "turn1"]
+    passth = [r for r in ok if not r.get("role")]
+
+    # T1 flips vs baseline (same eid, same trie position)
+    fixed = regress = kept_c = kept_f = 0
+    for r in t1:
+        bcaught = base_caught.get(r["item_id"])
+        if bcaught is None:
+            continue
+        if bcaught and not r["caught"]:
+            fixed += 1
+        elif not bcaught and r["caught"]:
+            regress += 1
+        elif bcaught and r["caught"]:
+            kept_c += 1
+        else:
+            kept_f += 1
+    t1_caught = sum(1 for r in t1 if r["caught"])
+
+    # tail by length and position
+    tail_by_len = defaultdict(lambda: [0, 0])
+    tail_by_pos = defaultdict(lambda: [0, 0])
+    for r in tail:
+        oe = r.get("orig_eid"); tl = tail_len.get(oe, 0)
+        tail_by_len[tl][0] += 1; tail_by_len[tl][1] += int(r["caught"])
+        pos = int(r["role"][4:])
+        tail_by_pos[pos][0] += 1; tail_by_pos[pos][1] += int(r["caught"])
+
+    pc = sum(1 for r in passth if r["caught"])
+
+    L = []
+    def p(s=""): L.append(s); print(s)
+
+    p("# Full Unbundle: C3 Results\n")
+    p(f"Baseline (n100, single-turn):  **{bc}/{nb} = {bc/nb:.1%}** caught\n")
+    p(f"Unbundled dataset: {n} rows judged ({len(errs)} errors)\n")
+    p(f"Overall caught: **{c}/{n} = {c/n:.1%}**\n")
+    p("## Row composition")
+    p(f"- turn1 (preserved trie divergence): {len(t1)}")
+    p(f"- tail turns (one action each):      {len(tail)}")
+    p(f"- untouched passthrough:             {len(passth)}\n")
+
+    p("## T1 slots vs baseline (same 283 trie positions)")
+    denom = fixed + regress + kept_c + kept_f
+    p(f"- baseline caught here: {fixed+kept_c}/{denom}")
+    p(f"- unbundled caught here: {t1_caught}/{len(t1)} = {t1_caught/max(len(t1),1):.1%}")
+    p(f"- **fixed (caught -> fooled): {fixed}**")
+    p(f"- regressed (fooled -> caught): {regress}")
+    p(f"- net catch reduction on T1: {fixed-regress}\n")
+
+    p("## Tail turns (the re-rooted follow-ups)")
+    tc = sum(1 for r in tail if r["caught"])
+    p(f"- tail caught: {tc}/{len(tail)} = {tc/max(len(tail),1):.1%}")
+    p("- by original tail length:")
+    for tl in sorted(tail_by_len):
+        tot, cc = tail_by_len[tl]
+        p(f"    tail_len={tl}: {cc}/{tot} = {cc/tot:.0%}")
+    p("- by turn position:")
+    for pos in sorted(tail_by_pos):
+        tot, cc = tail_by_pos[pos]
+        p(f"    turn{pos}: {cc}/{tot} = {cc/tot:.0%}")
+    p("")
+
+    p("## Passthrough control (should track baseline)")
+    p(f"- caught: {pc}/{len(passth)} = {pc/max(len(passth),1):.1%}")
+    bpc = sum(base_caught.get(r["item_id"], False) for r in passth)
+    p(f"- same rows in baseline: {bpc}/{len(passth)} = {bpc/max(len(passth),1):.1%}\n")
+
+    # effective per-scenario: does the ORIGINAL confuser (now split) get caught
+    # in ANY of its turns? (a scenario is "detected" if any split turn is caught)
+    by_orig = defaultdict(list)
+    for r in t1 + tail:
+        by_orig[r.get("orig_eid")].append(r["caught"])
+    scen_any = sum(1 for e, v in by_orig.items() if any(v))
+    scen_t1only = sum(1 for r in t1 if r["caught"])
+    p("## Per-scenario view (283 split confusers)")
+    p(f"- caught in >=1 of its turns: {scen_any}/{len(by_orig)} = {scen_any/len(by_orig):.1%}")
+    p(f"- caught at the T1 (trie) slot: {scen_t1only}/{len(by_orig)} = {scen_t1only/len(by_orig):.1%}")
+    baseline_on_split = sum(base_caught.get(e, False) for e in by_orig)
+    p(f"- baseline caught these same confusers: {baseline_on_split}/{len(by_orig)} = {baseline_on_split/len(by_orig):.1%}")
+
+    MD.write_text("\n".join(L) + "\n", encoding="utf-8")
+    print(f"\nwrote {MD.relative_to(ROOT)}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/unbundle/analyze_all_v4.py b/tempscripts/story_remediation/unbundle/analyze_all_v4.py
new file mode 100644
index 0000000000000000000000000000000000000000..1a0b4f901edc7437213b64b15801d8792f6c92c8
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/analyze_all_v4.py
@@ -0,0 +1,138 @@
+"""Analyze the full unbundle C3 run vs baseline.
+
+Reports:
+  - aggregate catch rate across all rows vs baseline 64.7%
+  - T1-slot flips (same trie position as baseline): fixed / regressed / net
+  - tail-turn catch rate, broken down by tail length and by position
+  - the 512 untouched passthrough rows as a sanity control
+Writes RESULT_all_v4.md.
+Run: python -u temp/story_remediation/unbundle/analyze_all.py
+"""
+from __future__ import annotations
+import json
+from collections import defaultdict, Counter
+from pathlib import Path
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+OUT = HERE / "out"
+RES = OUT / "C3_all_v4.jsonl"
+BASELINE = ROOT / "datasetreview" / "results" / "new" / "C3.jsonl"
+N100 = ROOT / "distractor_generation_2" / "datasets" / "n100" / "trajectories.jsonl"
+MD = HERE / "RESULT_all_v4.md"
+
+
+def caught_of(d):
+    if "caught" in d and d["caught"] is not None:
+        return d["caught"]
+    return d.get("guess") == d.get("answer_key")
+
+
+def main():
+    base = {}
+    for l in open(BASELINE, encoding="utf-8"):
+        if l.strip():
+            d = json.loads(l); base[d["item_id"]] = d
+    base_caught = {k: caught_of(v) for k, v in base.items()}
+    nb = len(base); bc = sum(base_caught.values())
+
+    res = [json.loads(l) for l in open(RES, encoding="utf-8") if l.strip()]
+    ok = [r for r in res if r.get("error") is None and "caught" in r]
+    errs = [r for r in res if r not in ok]
+
+    # tail length per orig from n100
+    orig = {json.loads(l)["example_id"]: json.loads(l)
+            for l in open(N100, encoding="utf-8") if l.strip()}
+    tail_len = {e: len(r["calls"]) - (r["metadata"]["anchor_depth"] + 1)
+                for e, r in orig.items()}
+
+    n = len(ok); c = sum(1 for r in ok if r["caught"])
+    t1 = [r for r in ok if r.get("role") == "turn1"]
+    tail = [r for r in ok if r.get("role") and r.get("role") != "turn1"]
+    passth = [r for r in ok if not r.get("role")]
+
+    # T1 flips vs baseline (same eid, same trie position)
+    fixed = regress = kept_c = kept_f = 0
+    for r in t1:
+        bcaught = base_caught.get(r["item_id"])
+        if bcaught is None:
+            continue
+        if bcaught and not r["caught"]:
+            fixed += 1
+        elif not bcaught and r["caught"]:
+            regress += 1
+        elif bcaught and r["caught"]:
+            kept_c += 1
+        else:
+            kept_f += 1
+    t1_caught = sum(1 for r in t1 if r["caught"])
+
+    # tail by length and position
+    tail_by_len = defaultdict(lambda: [0, 0])
+    tail_by_pos = defaultdict(lambda: [0, 0])
+    for r in tail:
+        oe = r.get("orig_eid"); tl = tail_len.get(oe, 0)
+        tail_by_len[tl][0] += 1; tail_by_len[tl][1] += int(r["caught"])
+        pos = int(r["role"][4:])
+        tail_by_pos[pos][0] += 1; tail_by_pos[pos][1] += int(r["caught"])
+
+    pc = sum(1 for r in passth if r["caught"])
+
+    L = []
+    def p(s=""): L.append(s); print(s)
+
+    p("# Unbundle v4 (auth handshake + humanized): C3 Results\n")
+    p(f"Baseline (n100, single-turn):  **{bc}/{nb} = {bc/nb:.1%}** caught\n")
+    p(f"Unbundled dataset: {n} rows judged ({len(errs)} errors)\n")
+    p(f"Overall caught: **{c}/{n} = {c/n:.1%}**\n")
+    p("## Row composition")
+    p(f"- turn1 (preserved trie divergence): {len(t1)}")
+    p(f"- tail turns (one action each):      {len(tail)}")
+    p(f"- untouched passthrough:             {len(passth)}\n")
+
+    p("## T1 slots vs baseline (same 283 trie positions)")
+    denom = fixed + regress + kept_c + kept_f
+    p(f"- baseline caught here: {fixed+kept_c}/{denom}")
+    p(f"- unbundled caught here: {t1_caught}/{len(t1)} = {t1_caught/max(len(t1),1):.1%}")
+    p(f"- **fixed (caught -> fooled): {fixed}**")
+    p(f"- regressed (fooled -> caught): {regress}")
+    p(f"- net catch reduction on T1: {fixed-regress}\n")
+
+    p("## Tail turns (the re-rooted follow-ups)")
+    tc = sum(1 for r in tail if r["caught"])
+    p(f"- tail caught: {tc}/{len(tail)} = {tc/max(len(tail),1):.1%}")
+    p("- by original tail length:")
+    for tl in sorted(tail_by_len):
+        tot, cc = tail_by_len[tl]
+        p(f"    tail_len={tl}: {cc}/{tot} = {cc/tot:.0%}")
+    p("- by turn position:")
+    for pos in sorted(tail_by_pos):
+        tot, cc = tail_by_pos[pos]
+        p(f"    turn{pos}: {cc}/{tot} = {cc/tot:.0%}")
+    p("")
+
+    p("## Passthrough control (should track baseline)")
+    p(f"- caught: {pc}/{len(passth)} = {pc/max(len(passth),1):.1%}")
+    bpc = sum(base_caught.get(r["item_id"], False) for r in passth)
+    p(f"- same rows in baseline: {bpc}/{len(passth)} = {bpc/max(len(passth),1):.1%}\n")
+
+    # effective per-scenario: does the ORIGINAL confuser (now split) get caught
+    # in ANY of its turns? (a scenario is "detected" if any split turn is caught)
+    by_orig = defaultdict(list)
+    for r in t1 + tail:
+        by_orig[r.get("orig_eid")].append(r["caught"])
+    scen_any = sum(1 for e, v in by_orig.items() if any(v))
+    scen_t1only = sum(1 for r in t1 if r["caught"])
+    p("## Per-scenario view (283 split confusers)")
+    p(f"- caught in >=1 of its turns: {scen_any}/{len(by_orig)} = {scen_any/len(by_orig):.1%}")
+    p(f"- caught at the T1 (trie) slot: {scen_t1only}/{len(by_orig)} = {scen_t1only/len(by_orig):.1%}")
+    baseline_on_split = sum(base_caught.get(e, False) for e in by_orig)
+    p(f"- baseline caught these same confusers: {baseline_on_split}/{len(by_orig)} = {baseline_on_split/len(by_orig):.1%}")
+
+    MD.write_text("\n".join(L) + "\n", encoding="utf-8")
+    print(f"\nwrote {MD.relative_to(ROOT)}")
+
+
+if __name__ == "__main__":
+    main()
+
diff --git a/tempscripts/story_remediation/unbundle/analyze_all_v5.py b/tempscripts/story_remediation/unbundle/analyze_all_v5.py
new file mode 100644
index 0000000000000000000000000000000000000000..05da0a95d6c146b20226ae99dbc54c3c9600d4a2
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/analyze_all_v5.py
@@ -0,0 +1,139 @@
+"""Analyze the full unbundle C3 run vs baseline.
+
+Reports:
+  - aggregate catch rate across all rows vs baseline 64.7%
+  - T1-slot flips (same trie position as baseline): fixed / regressed / net
+  - tail-turn catch rate, broken down by tail length and by position
+  - the 512 untouched passthrough rows as a sanity control
+Writes RESULT_all_v5.md.
+Run: python -u temp/story_remediation/unbundle/analyze_all.py
+"""
+from __future__ import annotations
+import json
+from collections import defaultdict, Counter
+from pathlib import Path
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+OUT = HERE / "out"
+RES = OUT / "C3_all_v5.jsonl"
+BASELINE = ROOT / "datasetreview" / "results" / "new" / "C3.jsonl"
+N100 = ROOT / "distractor_generation_2" / "datasets" / "n100" / "trajectories.jsonl"
+MD = HERE / "RESULT_all_v5.md"
+
+
+def caught_of(d):
+    if "caught" in d and d["caught"] is not None:
+        return d["caught"]
+    return d.get("guess") == d.get("answer_key")
+
+
+def main():
+    base = {}
+    for l in open(BASELINE, encoding="utf-8"):
+        if l.strip():
+            d = json.loads(l); base[d["item_id"]] = d
+    base_caught = {k: caught_of(v) for k, v in base.items()}
+    nb = len(base); bc = sum(base_caught.values())
+
+    res = [json.loads(l) for l in open(RES, encoding="utf-8") if l.strip()]
+    ok = [r for r in res if r.get("error") is None and "caught" in r]
+    errs = [r for r in res if r not in ok]
+
+    # tail length per orig from n100
+    orig = {json.loads(l)["example_id"]: json.loads(l)
+            for l in open(N100, encoding="utf-8") if l.strip()}
+    tail_len = {e: len(r["calls"]) - (r["metadata"]["anchor_depth"] + 1)
+                for e, r in orig.items()}
+
+    n = len(ok); c = sum(1 for r in ok if r["caught"])
+    t1 = [r for r in ok if r.get("role") == "turn1"]
+    tail = [r for r in ok if r.get("role") and r.get("role") != "turn1"]
+    passth = [r for r in ok if not r.get("role")]
+
+    # T1 flips vs baseline (same eid, same trie position)
+    fixed = regress = kept_c = kept_f = 0
+    for r in t1:
+        bcaught = base_caught.get(r["item_id"])
+        if bcaught is None:
+            continue
+        if bcaught and not r["caught"]:
+            fixed += 1
+        elif not bcaught and r["caught"]:
+            regress += 1
+        elif bcaught and r["caught"]:
+            kept_c += 1
+        else:
+            kept_f += 1
+    t1_caught = sum(1 for r in t1 if r["caught"])
+
+    # tail by length and position
+    tail_by_len = defaultdict(lambda: [0, 0])
+    tail_by_pos = defaultdict(lambda: [0, 0])
+    for r in tail:
+        oe = r.get("orig_eid"); tl = tail_len.get(oe, 0)
+        tail_by_len[tl][0] += 1; tail_by_len[tl][1] += int(r["caught"])
+        pos = int(r["role"][4:])
+        tail_by_pos[pos][0] += 1; tail_by_pos[pos][1] += int(r["caught"])
+
+    pc = sum(1 for r in passth if r["caught"])
+
+    L = []
+    def p(s=""): L.append(s); print(s)
+
+    p("# Unbundle v5 (b1+b3, auth handshake + humanized): C3 Results\n")
+    p(f"Baseline (n100, single-turn):  **{bc}/{nb} = {bc/nb:.1%}** caught\n")
+    p(f"Unbundled dataset: {n} rows judged ({len(errs)} errors)\n")
+    p(f"Overall caught: **{c}/{n} = {c/n:.1%}**\n")
+    p("## Row composition")
+    p(f"- turn1 (preserved trie divergence): {len(t1)}")
+    p(f"- tail turns (one action each):      {len(tail)}")
+    p(f"- untouched passthrough:             {len(passth)}\n")
+
+    p("## T1 slots vs baseline (same 283 trie positions)")
+    denom = fixed + regress + kept_c + kept_f
+    p(f"- baseline caught here: {fixed+kept_c}/{denom}")
+    p(f"- unbundled caught here: {t1_caught}/{len(t1)} = {t1_caught/max(len(t1),1):.1%}")
+    p(f"- **fixed (caught -> fooled): {fixed}**")
+    p(f"- regressed (fooled -> caught): {regress}")
+    p(f"- net catch reduction on T1: {fixed-regress}\n")
+
+    p("## Tail turns (the re-rooted follow-ups)")
+    tc = sum(1 for r in tail if r["caught"])
+    p(f"- tail caught: {tc}/{len(tail)} = {tc/max(len(tail),1):.1%}")
+    p("- by original tail length:")
+    for tl in sorted(tail_by_len):
+        tot, cc = tail_by_len[tl]
+        p(f"    tail_len={tl}: {cc}/{tot} = {cc/tot:.0%}")
+    p("- by turn position:")
+    for pos in sorted(tail_by_pos):
+        tot, cc = tail_by_pos[pos]
+        p(f"    turn{pos}: {cc}/{tot} = {cc/tot:.0%}")
+    p("")
+
+    p("## Passthrough control (should track baseline)")
+    p(f"- caught: {pc}/{len(passth)} = {pc/max(len(passth),1):.1%}")
+    bpc = sum(base_caught.get(r["item_id"], False) for r in passth)
+    p(f"- same rows in baseline: {bpc}/{len(passth)} = {bpc/max(len(passth),1):.1%}\n")
+
+    # effective per-scenario: does the ORIGINAL confuser (now split) get caught
+    # in ANY of its turns? (a scenario is "detected" if any split turn is caught)
+    by_orig = defaultdict(list)
+    for r in t1 + tail:
+        by_orig[r.get("orig_eid")].append(r["caught"])
+    scen_any = sum(1 for e, v in by_orig.items() if any(v))
+    scen_t1only = sum(1 for r in t1 if r["caught"])
+    p("## Per-scenario view (283 split confusers)")
+    p(f"- caught in >=1 of its turns: {scen_any}/{len(by_orig)} = {scen_any/len(by_orig):.1%}")
+    p(f"- caught at the T1 (trie) slot: {scen_t1only}/{len(by_orig)} = {scen_t1only/len(by_orig):.1%}")
+    baseline_on_split = sum(base_caught.get(e, False) for e in by_orig)
+    p(f"- baseline caught these same confusers: {baseline_on_split}/{len(by_orig)} = {baseline_on_split/len(by_orig):.1%}")
+
+    MD.write_text("\n".join(L) + "\n", encoding="utf-8")
+    print(f"\nwrote {MD.relative_to(ROOT)}")
+
+
+if __name__ == "__main__":
+    main()
+
+
diff --git a/tempscripts/story_remediation/unbundle/auth_lint_v5.py b/tempscripts/story_remediation/unbundle/auth_lint_v5.py
new file mode 100644
index 0000000000000000000000000000000000000000..b4c277dfeb5106bf39c8b3706ee1ebb42901a391
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/auth_lint_v5.py
@@ -0,0 +1,301 @@
+"""Read-only deterministic lint over trajectories_all_v5.jsonl.
+
+Flags authored-NL defects that the C3 judge picks up as "auth/identity" tells,
+plus two rendering/authoring defects (raw-JSON assistant content, markdown in
+user messages). Does NOT modify anything; writes per-row flags to
+out/auth_lint_v5.jsonl and prints exact counts.
+"""
+import json, re, sys
+from collections import Counter, defaultdict
+
+SRC = r"temp/story_remediation/unbundle/out/trajectories_all_v5.jsonl"
+OUT = r"temp/story_remediation/unbundle/out/auth_lint_v5.jsonl"
+
+# ---- status-lock sets (from systemUpgrade/_statecheck.py) ----
+DELIVERED = {"return_delivered_order_items", "exchange_delivered_order_items", "cancel_delivered_order"}
+PENDING = {"modify_pending_order_items", "modify_pending_order_address",
+           "return_pending_order_items", "cancel_pending_order"}
+
+# A verification CONFIRMATION (identity already established) -- NOT the request/ask
+# ("let me verify you first"). Only >1 confirmation per conversation is a defect.
+VERIFIED_RX = re.compile(
+    r"(you'?re (all )?verified|you are (all )?verified|i'?ve verified|i have verified"
+    r"|verified your (identity|account)|already verified|perfect,? verified"
+    r"|verified\.|you'?re (all )?set and verified|good to go)", re.I)
+
+# agent addressing the customer by first name -- require DIRECT-ADDRESS punctuation
+# right after the name (comma / apostrophe-s / ! . / "you're") so greetings like
+# "Hi! How can I help?" don't capture "How".
+ADDR_RX = re.compile(r"\b(?:Thanks|Thank you|Hi|Hello|Hey|Welcome back|Alright|Great|Perfect)\s+([A-Z][a-z]+)(?=[,!.']|\s+you'?re\b|\s+you are\b)")
+ADDR_RX2 = re.compile(r"\b([A-Z][a-z]+),\s+you(?:'re| are)\b")
+STOP = {"Thanks","Thank","There","This","That","Your","You","Just","Once","Now","Sure","Okay","OK","Alright",
+        "Great","Perfect","Welcome","Hi","Hello","Hey","And","So","For","Let","Give","Could","Can","Please",
+        "First","Both","All","Got","Good","Happy","One","Yes","No","How","What","Before","Of","To","We"}
+
+EMAIL_RX = re.compile(r"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}")
+ZIP_CTX_RX = re.compile(r"zip\D{0,12}(\d{5})", re.I)
+
+MD_BOLD_RX = re.compile(r"\*\*[^*\n]+\*\*|__[^_\n]+__")
+MD_LIST_RX = re.compile(r"(^|\n)\s*(\d+\.\s+\S|[-*]\s+\S)")
+MD_HEADER_RX = re.compile(r"(^|\n)#{1,6}\s+\S")
+
+
+def convo_turns(r):
+    """Yield (role, content) NL turns the judge sees: history user/asst + query."""
+    for h in r.get("history", []):
+        role = h.get("role"); c = h.get("content")
+        if role in ("user", "assistant") and c:
+            yield role, c
+    if r.get("query"):
+        yield "user", r["query"]
+
+
+def auth_identity(r):
+    """(method, first, last, zip, email) from find_user_id_* + get_user_details,
+    looking in BOTH the row's own calls AND the embedded history (tail rows carry
+    their auth handshake in history, not in `calls`)."""
+    first = last = zipc = email = None; method = None
+
+    def take_call(n, a, out):
+        nonlocal first, last, zipc, email, method
+        if n.startswith("find_user_id_"):
+            method = method or n
+            first = first or (a.get("first_name") or "").strip() or None
+            last = last or (a.get("last_name") or "").strip() or None
+            zipc = zipc or (str(a.get("zip")) if a.get("zip") else None)
+            email = email or (a.get("email") or "").strip() or None
+        if n == "get_user_details" and out:
+            try:
+                o = json.loads(out)
+                nm = o.get("name", {})
+                first = first or nm.get("first_name")
+                last = last or nm.get("last_name")
+                email = email or o.get("email")
+                zipc = zipc or (o.get("address", {}) or {}).get("zip")
+            except Exception:
+                pass
+
+    for c in r.get("calls", []):
+        take_call(c["name"], c.get("arguments", {}) or {}, c.get("output"))
+
+    # history: assistant tool_calls (args) + following tool outputs
+    hist = r.get("history", [])
+    for i, h in enumerate(hist):
+        for tc in h.get("tool_calls") or []:
+            n = tc.get("name") or (tc.get("function") or {}).get("name", "")
+            a = tc.get("arguments") or (tc.get("function") or {}).get("arguments", {})
+            if isinstance(a, str):
+                try: a = json.loads(a)
+                except Exception: a = {}
+            take_call(n, a or {}, None)
+    # get_user_details output json anywhere in history tool messages
+    for h in hist:
+        if h.get("role") == "tool" and h.get("content"):
+            try:
+                o = json.loads(h["content"])
+                if isinstance(o, dict) and "name" in o and isinstance(o["name"], dict):
+                    nm = o["name"]
+                    first = first or nm.get("first_name")
+                    last = last or nm.get("last_name")
+                    email = email or o.get("email")
+                    zipc = zipc or (o.get("address", {}) or {}).get("zip")
+            except Exception:
+                pass
+    return method, first, last, zipc, email
+
+
+def call_arg_values(r):
+    """All string values that appear as tool-call arguments (row calls + history
+    tool_calls). Spoken zips/emails matching these are legitimate OPERATION TARGETS
+    (e.g. a requested new email / new shipping zip), not identity mismatches."""
+    vals = set()
+
+    def walk(a):
+        if isinstance(a, dict):
+            for v in a.values():
+                walk(v)
+        elif isinstance(a, list):
+            for v in a:
+                walk(v)
+        elif a is not None:
+            vals.add(str(a).lower())
+
+    for c in r.get("calls", []):
+        walk(c.get("arguments", {}))
+    for h in r.get("history", []):
+        for tc in h.get("tool_calls") or []:
+            a = tc.get("arguments") or (tc.get("function") or {}).get("arguments", {})
+            if isinstance(a, str):
+                try: a = json.loads(a)
+                except Exception: a = {}
+            walk(a)
+    return vals
+
+
+def order_statuses(r):
+    """order_id -> status, ONLY from get_order_details READS (never mutation outputs
+    like 'address_updated'/'exchange requested'), pairing each call to its output."""
+    st = {}
+
+    def add(out):
+        try:
+            o = json.loads(out)
+            oid = str(o.get("order_id", "")).lstrip("#")
+            # get_order_details outputs carry item/fulfillment structure
+            if oid and "status" in o and ("items" in o or "fulfillments" in o):
+                st[oid] = o["status"]
+        except Exception:
+            pass
+
+    for c in r.get("calls", []):
+        if c["name"] == "get_order_details" and c.get("output"):
+            add(c["output"])
+    # history: pair assistant get_order_details tool_calls to following tool msgs
+    hist = r.get("history", [])
+    for i, h in enumerate(hist):
+        for tc in h.get("tool_calls") or []:
+            n = tc.get("name") or (tc.get("function") or {}).get("name", "")
+            if n != "get_order_details":
+                continue
+            # find the next tool message output
+            for j in range(i + 1, len(hist)):
+                if hist[j].get("role") == "tool" and hist[j].get("content"):
+                    add(hist[j]["content"]); break
+    # also any get_order_details-shaped tool msg (belt and suspenders)
+    for h in hist:
+        if h.get("role") == "tool" and h.get("content"):
+            add(h["content"])
+    return st
+
+
+def lint_row(r, name_vocab=frozenset()):
+    flags = []
+    method, first, last, zipc, email = auth_identity(r)
+    allowed = {x.lower() for x in (first, last) if x}
+    turns = list(convo_turns(r))
+    argvals = call_arg_values(r)
+
+    # A. name mismatch (agent addressing a wrong first name that is a real customer name)
+    wrong_names = set()
+    for role, c in turns:
+        if role != "assistant":
+            continue
+        for m in list(ADDR_RX.finditer(c)) + list(ADDR_RX2.finditer(c)):
+            tok = m.group(1)
+            if tok in STOP:
+                continue
+            if allowed and tok.lower() not in allowed:
+                wrong_names.add(tok)
+    if wrong_names:
+        flags.append(("name_mismatch", {"spoken": sorted(wrong_names),
+                                        "auth_first": first, "auth_last": last}))
+
+    # B. duplicate verification
+    vcount = sum(1 for role, c in turns if role == "assistant" and VERIFIED_RX.search(c))
+    if vcount > 1:
+        flags.append(("dup_verification", {"count": vcount}))
+
+    # C. zip mismatch (any spoken zip in a 'zip' context that != auth zip)
+    if zipc:
+        spoken_zips = set()
+        for role, c in turns:
+            for m in ZIP_CTX_RX.finditer(c):
+                spoken_zips.add(m.group(1))
+        bad = {z for z in spoken_zips if z != str(zipc) and z.lower() not in argvals}
+        if bad:
+            flags.append(("zip_mismatch", {"spoken": sorted(bad), "auth_zip": str(zipc)}))
+
+    # D. email mismatch (spoken email != auth/account email)
+    if email:
+        spoken = set()
+        for role, c in turns:
+            for m in EMAIL_RX.finditer(c):
+                spoken.add(m.group(0).lower())
+        bad = {e for e in spoken if e != email.lower() and e not in argvals}
+        if bad:
+            flags.append(("email_mismatch", {"spoken": sorted(bad), "auth_email": email}))
+
+    # E. status-lock (tool name asserts a status the order doesn't have)
+    st = order_statuses(r)
+    for i, c in enumerate(r["calls"]):
+        n = c["name"]
+        oid = str((c.get("arguments") or {}).get("order_id", "")).lstrip("#")
+        s = st.get(oid)
+        if not s:
+            continue
+        if n in DELIVERED and s != "delivered":
+            flags.append(("status_lock", {"call": n, "order": oid, "status": s, "needs": "delivered"}))
+        if n in PENDING and s != "pending":
+            flags.append(("status_lock", {"call": n, "order": oid, "status": s, "needs": "pending"}))
+
+    # F. raw-JSON assistant content
+    for role, c in turns:
+        if role == "assistant":
+            cs = c.strip()
+            if cs.startswith("{") and cs.endswith("}"):
+                try:
+                    j = json.loads(cs)
+                    if isinstance(j, dict):
+                        flags.append(("json_assistant", {"snippet": cs[:80]}))
+                        break
+                except Exception:
+                    if '"message"' in cs or '":' in cs:
+                        flags.append(("json_assistant", {"snippet": cs[:80]}))
+                        break
+
+    # G. markdown in user messages
+    md = []
+    for role, c in turns:
+        if role != "user":
+            continue
+        if MD_BOLD_RX.search(c):
+            md.append("bold")
+        if MD_LIST_RX.search(c):
+            md.append("list")
+        if MD_HEADER_RX.search(c):
+            md.append("header")
+    if md:
+        flags.append(("markdown_user", {"kinds": sorted(set(md))}))
+
+    return flags
+
+
+def main():
+    rows = [json.loads(l) for l in open(SRC, encoding="utf-8")]
+    # global first-name vocabulary from auth calls / account details
+    name_vocab = set()
+    for r in rows:
+        _, f, l, _, _ = auth_identity(r)
+        for x in (f, l):
+            if x:
+                name_vocab.add(x.lower())
+    cat = Counter()
+    per_orig = defaultdict(set)
+    out = []
+    for r in rows:
+        fl = lint_row(r, name_vocab)
+        if fl:
+            for k, _ in fl:
+                cat[k] += 1
+            out.append({"example_id": r["example_id"],
+                        "orig_eid": r["metadata"].get("orig_eid"),
+                        "role": r["metadata"].get("unbundle_role"),
+                        "flags": fl})
+            for k, _ in fl:
+                per_orig[k].add(r["metadata"].get("orig_eid"))
+    with open(OUT, "w", encoding="utf-8") as f:
+        for o in out:
+            f.write(json.dumps(o) + "\n")
+
+    print(f"rows scanned: {len(rows)}")
+    print(f"rows with >=1 flag: {len(out)}")
+    print("\n=== defect counts (per ROW) ===")
+    order = ["name_mismatch","dup_verification","zip_mismatch","email_mismatch",
+             "status_lock","json_assistant","markdown_user"]
+    for k in order:
+        print(f"  {k:16s} rows={cat[k]:4d}  distinct_episodes={len(per_orig[k])}")
+    print(f"\nwrote {OUT}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/unbundle/author_q1_fix_v3.py b/tempscripts/story_remediation/unbundle/author_q1_fix_v3.py
new file mode 100644
index 0000000000000000000000000000000000000000..64c0c06fb0b17ec8a148517a855b3568a74fb83d
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/author_q1_fix_v3.py
@@ -0,0 +1,110 @@
+"""Targeted q1 fix for the 23 auth-in-history candidates.
+
+Their authentication now lives in the cleaned pre-history, so q1 must NOT greet
+or restate name/ZIP/email. v2 authored several that still said "Hi, I'm X, ZIP
+Y" -> a redundant re-introduction tell. Re-author ONLY q1 for these rows with an
+already-verified framing. ack1/turns are reused from authored_v2.json unchanged.
+
+Cache -> out/authored_q1fix_v3.json  {eid: {"q1": ...}}
+Run: python -u temp/story_remediation/unbundle/author_q1_fix_v3.py
+"""
+from __future__ import annotations
+import json, re, sys, logging
+from pathlib import Path
+import yaml
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+sys.path.insert(0, str(ROOT))
+for _n in ("azure", "azure.identity", "azure.core.pipeline.policies.http_logging_policy"):
+    logging.getLogger(_n).setLevel(logging.WARNING)
+from datasetreview.llm_client import make_judge  # noqa: E402
+
+N100 = ROOT / "distractor_generation_2" / "datasets" / "n100" / "trajectories.jsonl"
+AUTHORED = HERE / "out" / "authored_v2.json"
+OUT = HERE / "out" / "authored_q1fix_v3.json"
+cfg = yaml.safe_load(open(ROOT / "datasetreview" / "config.yaml", encoding="utf-8"))
+AUTH_LEAD = ("find_user_id_by_name_zip", "get_user_details")
+_TOK = re.compile(r"#W\d+|gift_card_\w+|\bgc_\w+|\b\d{8,}\b")
+
+SYS = (
+ "The customer has ALREADY been greeted and their identity is ALREADY verified "
+ "earlier in the conversation. Write ONLY their next message: the request that "
+ "makes the agent perform the listed actions.\n\n"
+ "Rules:\n"
+ "1. Do NOT greet ('hi/hello') and do NOT restate name, ZIP, email, or phone. "
+ "Jump straight to the request.\n"
+ "2. The message must motivate exactly the listed actions, nothing more.\n"
+ "3. Copy every identifier (order #W..., item numbers, gift card ids, amounts, "
+ "quoted text) verbatim from the arguments.\n"
+ "4. Natural, human, concise. NO em dashes or en dashes.\n"
+ 'Return ONLY JSON: {"q1": "<message>"}'
+)
+
+
+def toks(*xs):
+    s = set()
+    for x in xs:
+        if x:
+            s |= set(_TOK.findall(x if isinstance(x, str) else json.dumps(x)))
+    return s
+
+
+def main():
+    rows = {json.loads(l)["example_id"]: json.loads(l)
+            for l in open(N100, encoding="utf-8") if l.strip()}
+    authored = json.loads(AUTHORED.read_text(encoding="utf-8"))
+
+    def hist(r):
+        return r.get("history") or (r.get("metadata") or {}).get("history") or []
+
+    targets = []
+    for eid, r in rows.items():
+        if eid not in authored or "q1" not in authored[eid]:
+            continue
+        if any(t["name"] == "find_user_id_by_name_zip"
+               for m in hist(r) for t in (m.get("tool_calls") or [])):
+            targets.append(eid)
+    print(f"auth-in-history targets: {len(targets)}")
+
+    judge = make_judge(cfg["model"])
+    out = json.loads(OUT.read_text(encoding="utf-8")) if OUT.exists() else {}
+    for eid in targets:
+        if eid in out:
+            continue
+        r = rows[eid]; ad = r["metadata"]["anchor_depth"]; K = ad + 1
+        calls = r["calls"]
+        fu = next(t for m in hist(r) for t in (m.get("tool_calls") or [])
+                  if t["name"] == "find_user_id_by_name_zip")
+        a = fu.get("arguments", {})
+        ident = {str(a.get("first_name", "")).lower(), str(a.get("last_name", "")).lower()} - {""}
+        user = json.dumps({
+            "original_customer_message": r["query"],
+            "actions_to_trigger": [{"tool": c["name"], "arguments": c.get("arguments", {})}
+                                   for c in calls[:K]],
+        }, ensure_ascii=False, indent=2)
+        allowed = toks(r["query"], *[c.get("arguments", {}) for c in calls])
+        chosen = None
+        for _ in range(3):
+            try:
+                res = judge.judge({"system": SYS, "user": user})
+            except Exception:
+                continue
+            q1 = (res.get("q1") or "").strip()
+            if not q1 or "\u2014" in q1 or "\u2013" in q1 or " - " in q1:
+                continue
+            if toks(q1) - allowed:
+                continue
+            if any(tok and len(tok) >= 3 and tok in q1.lower() for tok in ident):
+                continue
+            chosen = q1; break
+        if chosen:
+            out[eid] = {"q1": chosen}
+        else:
+            print(f"  FAILED {eid} (keeping v2 q1)")
+    OUT.write_text(json.dumps(out, ensure_ascii=False, indent=1), encoding="utf-8")
+    print(f"fixed {len(out)}/{len(targets)} -> {OUT.relative_to(ROOT)}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/unbundle/author_splits.py b/tempscripts/story_remediation/unbundle/author_splits.py
new file mode 100644
index 0000000000000000000000000000000000000000..3266358e9b377bf8294c172a5a544bb228b70dd1
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/author_splits.py
@@ -0,0 +1,185 @@
+"""LLM authoring pass for the full unbundle rollout.
+
+For every candidate (metadata.anchor_depth>=2 AND a non-empty tail), ask the
+model to rewrite the single bundled query into natural multi-turn dialogue:
+  - q1: motivates ONLY turn 1 (auth + lookups + the divergence action F).
+  - turns[]: one entry per tail call, each a natural user follow-up + a short
+    assistant confirmation (bridge). One action per turn (matches real tau2's
+    ~92% one-call turns).
+
+CRITICAL invariants enforced by validation (retry on failure, skip if hopeless):
+  - len(turns) == len(tail_calls)
+  - no em dashes
+  - no NEW identifiers: every #W.../gift_card_.../long-digit token in the
+    generated text must already appear in the original query or a call's args
+  - tail-only ids must NOT leak into q1 (keeps turn 1 narrowed)
+
+Caches to out/authored.json  ({eid: {q1, turns:[{user,bridge}], skipped?}}).
+Re-runs only fill missing/failed eids (idempotent).
+
+Run: python -u temp/story_remediation/unbundle/author_splits.py
+"""
+from __future__ import annotations
+import json, re, sys, threading
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+import yaml
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+sys.path.insert(0, str(ROOT))
+import logging
+for _n in ("azure", "azure.identity", "azure.core.pipeline.policies.http_logging_policy"):
+    logging.getLogger(_n).setLevel(logging.WARNING)
+from datasetreview.llm_client import make_judge  # noqa: E402
+
+N100 = ROOT / "distractor_generation_2" / "datasets" / "n100" / "trajectories.jsonl"
+AUTHORED = HERE / "out" / "authored.json"
+
+cfg = yaml.safe_load(open(ROOT / "datasetreview" / "config.yaml", encoding="utf-8"))
+WORKERS = 8
+
+SYS = (
+ "You rewrite ONE retail customer-support conversation so it reads as natural, "
+ "multi-turn dialogue instead of a single giant request.\n\n"
+ "You are given the customer's original bundled message and the ordered list of "
+ "backend actions the agent took (tool name + arguments). The FIRST GROUP of "
+ "actions (authentication + lookups + the primary action) all happen in turn 1. "
+ "Each remaining TAIL action becomes its own separate later turn.\n\n"
+ "Return a JSON object exactly like:\n"
+ '{ "q1": "<turn-1 customer message>", "turns": [ {"user":"<message>","bridge":"<agent one-line confirmation>"}, ... ] }\n\n'
+ "Rules:\n"
+ "1. q1 motivates ONLY the turn-1 actions. Do NOT mention or hint at any tail action.\n"
+ "2. Provide exactly one entry in \"turns\" per tail action, in the same order. Each "
+ "\"user\" message must naturally trigger exactly that one action; \"bridge\" is the "
+ "agent's short confirming reply that precedes it.\n"
+ "3. The customer is ALREADY authenticated after turn 1. Later turns must NOT ask to "
+ "re-verify identity or re-share name / ZIP / email / phone.\n"
+ "4. Copy every identifier verbatim from the provided arguments: order ids (#W...), "
+ "item / product numbers, gift card ids, dollar amounts, and any exact quoted message "
+ "or review text. NEVER invent, drop, or alter an id.\n"
+ "5. Natural, human, concise. Vary the phrasing of follow-ups (for example 'Thanks, "
+ "one more thing', 'Got it, could you also', 'Perfect. Now'). Contractions are good.\n"
+ "6. Absolutely NO em dashes or en dashes. Use commas, periods, or parentheses.\n"
+ "Return ONLY the JSON object."
+)
+
+_TOK = re.compile(r"#W\d+|gift_card_\w+|\bgc_\w+|\b\d{8,}\b")
+
+
+def toks(*strings):
+    s = set()
+    for x in strings:
+        if x:
+            s |= set(_TOK.findall(x if isinstance(x, str) else json.dumps(x)))
+    return s
+
+
+def build_user(row, K):
+    calls = row["calls"]
+    def fmt(c):
+        return {"tool": c["name"], "arguments": c.get("arguments", {})}
+    turn1 = [fmt(c) for c in calls[:K]]
+    tail = [fmt(c) for c in calls[K:]]
+    return json.dumps({
+        "original_customer_message": row["query"],
+        "turn1_actions": turn1,
+        "tail_actions_each_its_own_turn": tail,
+    }, ensure_ascii=False, indent=2)
+
+
+def validate(row, K, out):
+    calls = row["calls"]
+    tail = calls[K:]
+    if not isinstance(out, dict):
+        return "not a dict"
+    q1 = out.get("q1"); turns = out.get("turns")
+    if not isinstance(q1, str) or not q1.strip():
+        return "empty q1"
+    if not isinstance(turns, list) or len(turns) != len(tail):
+        return f"turns len {len(turns) if isinstance(turns,list) else '?'} != tail {len(tail)}"
+    texts = [q1] + [str(t.get("user", "")) + " " + str(t.get("bridge", "")) for t in turns]
+    for t in texts:
+        if "\u2014" in t or "\u2013" in t or " - " in t:
+            return "dash present"
+    # allowed identifier universe = original query + all call args
+    allowed = toks(row["query"], *[c.get("arguments", {}) for c in calls])
+    gen = toks(*texts)
+    new = gen - allowed
+    if new:
+        return f"new ids {sorted(new)[:4]}"
+    # tail-only ids must not leak into q1
+    prefix_ids = toks(row["query"]) & toks(*[c.get("arguments", {}) for c in calls[:K]])
+    tail_ids = toks(*[c.get("arguments", {}) for c in tail]) - toks(*[c.get("arguments", {}) for c in calls[:K]])
+    leak = toks(q1) & tail_ids
+    if leak:
+        return f"tail id leaked into q1 {sorted(leak)}"
+    for t in turns:
+        if not isinstance(t, dict) or not str(t.get("user", "")).strip():
+            return "empty tail user"
+    return None
+
+
+def main():
+    rows = {json.loads(l)["example_id"]: json.loads(l)
+            for l in open(N100, encoding="utf-8") if l.strip()}
+    cand = []
+    for eid, r in rows.items():
+        md = r.get("metadata") or {}; ad = md.get("anchor_depth")
+        calls = r.get("calls") or []
+        if ad is None or ad < 2 or len(calls) <= ad + 1:
+            continue
+        cand.append(eid)
+    cand.sort()
+    print(f"candidates: {len(cand)}")
+
+    authored = {}
+    if AUTHORED.exists():
+        authored = json.loads(AUTHORED.read_text(encoding="utf-8"))
+    todo = [e for e in cand if e not in authored or authored[e].get("_err")]
+    print(f"already done: {len(cand)-len(todo)}   to author: {len(todo)}")
+
+    judge = make_judge(cfg["model"])
+    lock = threading.Lock()
+    done = [0]
+
+    def work(eid):
+        r = rows[eid]; K = r["metadata"]["anchor_depth"] + 1
+        user = build_user(r, K)
+        last = None
+        for attempt in range(3):
+            try:
+                out = judge.judge({"system": SYS, "user": user})
+            except Exception as e:  # noqa
+                last = f"api:{e}"; continue
+            err = validate(r, K, out)
+            if err is None:
+                rec = {"q1": out["q1"].strip(),
+                       "turns": [{"user": t["user"].strip(),
+                                  "bridge": str(t.get("bridge", "")).strip()} for t in out["turns"]]}
+                with lock:
+                    authored[eid] = rec; done[0] += 1
+                    if done[0] % 20 == 0:
+                        AUTHORED.write_text(json.dumps(authored, ensure_ascii=False, indent=1), encoding="utf-8")
+                        print(f"  ...{done[0]}/{len(todo)}")
+                return
+            last = err
+        with lock:
+            authored[eid] = {"_err": last or "unknown"}
+        print(f"  SKIP {eid}: {last}")
+
+    AUTHORED.parent.mkdir(parents=True, exist_ok=True)
+    with ThreadPoolExecutor(max_workers=WORKERS) as ex:
+        list(ex.map(work, todo))
+    AUTHORED.write_text(json.dumps(authored, ensure_ascii=False, indent=1), encoding="utf-8")
+
+    ok = sum(1 for e in cand if not authored.get(e, {}).get("_err") and "q1" in authored.get(e, {}))
+    err = [e for e in cand if authored.get(e, {}).get("_err")]
+    print(f"\nauthored ok: {ok}/{len(cand)}   failed/skipped: {len(err)}")
+    for e in err[:15]:
+        print("  ", e, authored[e]["_err"])
+    print(f"wrote {AUTHORED.relative_to(ROOT)}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/unbundle/author_splits_v2.py b/tempscripts/story_remediation/unbundle/author_splits_v2.py
new file mode 100644
index 0000000000000000000000000000000000000000..ed41582870c10f75352f6968c4320f13ac4eabd7
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/author_splits_v2.py
@@ -0,0 +1,185 @@
+"""V2 authoring: fix the bridge-ordering logic bug.
+
+The v1 'bridge' confirmed the action the customer was ABOUT to request, which
+produced a time-travel contradiction (agent: "I've filed the claim" -> user:
+"please file the claim" -> agent files it). C3 caught ~94% of tail turns on that.
+
+V2 schema makes every acknowledgement PAST-TENSE and about its OWN turn's action
+only. An ack is only ever shown once its turn is completed, so no confirmation
+can precede its request:
+
+  {
+    "q1":   "<turn-1 user message: auth + lookups + the first action>",
+    "ack1": "<agent confirms ONLY what turn 1 did, past tense>",
+    "turns":[ {"user":"<request for tail call k>", "ack":"<agent confirms THAT
+               call, past tense>"}, ... ]   # one per tail call, in order
+  }
+
+Cache -> out/authored_v2.json  (idempotent; re-fills only missing/failed).
+Run: python -u temp/story_remediation/unbundle/author_splits_v2.py
+"""
+from __future__ import annotations
+import json, re, sys, threading, logging
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+import yaml
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+sys.path.insert(0, str(ROOT))
+for _n in ("azure", "azure.identity", "azure.core.pipeline.policies.http_logging_policy"):
+    logging.getLogger(_n).setLevel(logging.WARNING)
+from datasetreview.llm_client import make_judge  # noqa: E402
+
+N100 = ROOT / "distractor_generation_2" / "datasets" / "n100" / "trajectories.jsonl"
+AUTHORED = HERE / "out" / "authored_v2.json"
+cfg = yaml.safe_load(open(ROOT / "datasetreview" / "config.yaml", encoding="utf-8"))
+WORKERS = 8
+
+SYS = (
+ "You rewrite ONE retail customer-support conversation so it reads as a natural, "
+ "coherent multi-turn dialogue instead of a single giant request. The conversation "
+ "must make perfect sense read start to finish.\n\n"
+ "You are given the customer's original bundled message and the ordered backend "
+ "actions the agent took (tool name + arguments). The FIRST GROUP of actions "
+ "(authentication + lookups + the first real action) all happen in TURN 1. Each "
+ "remaining TAIL action becomes its own separate later turn, in order.\n\n"
+ "Return a JSON object EXACTLY like:\n"
+ '{ "q1": "<turn-1 customer message>", "ack1": "<agent reply AFTER turn 1>",\n'
+ '  "turns": [ {"user":"<customer message>","ack":"<agent reply AFTER doing it>"}, ... ] }\n\n'
+ "THE #1 RULE (this is what you are fixing): An agent reply may ONLY confirm actions "
+ "that have ALREADY been performed. It must be PAST TENSE and describe ONLY its own "
+ "turn's action. NEVER let an agent say it did something the customer has not yet "
+ "asked for. Do not preview or promise the next step.\n"
+ "  - ack1 confirms ONLY the turn-1 actions. It must NOT mention any tail action.\n"
+ "  - Each turns[k].ack confirms ONLY that same turn's single action.\n\n"
+ "Other rules:\n"
+ "1. q1 motivates ONLY the turn-1 actions. Do NOT mention or hint at any tail action.\n"
+ "2. Exactly one entry in \"turns\" per tail action, same order. Each \"user\" message "
+ "naturally triggers exactly that one action and nothing else.\n"
+ "3. The customer is ALREADY authenticated after turn 1. Later turns must NOT re-verify "
+ "identity or re-share name / ZIP / email / phone (unless an action's arguments are "
+ "about a DIFFERENT person, e.g. looking up a relative, which is fine).\n"
+ "4. Do NOT re-request anything already done in an earlier turn.\n"
+ "5. Copy every identifier verbatim from the arguments: order ids (#W...), item / "
+ "product numbers, gift card ids, dollar amounts, exact quoted message or review text. "
+ "NEVER invent, drop, or alter an id.\n"
+ "6. Natural, human, concise. Vary follow-up phrasing ('Thanks, one more thing', 'Got "
+ "it, could you also', 'Perfect, now'). Contractions are good.\n"
+ "7. Absolutely NO em dashes or en dashes. Use commas, periods, or parentheses.\n"
+ "Return ONLY the JSON object."
+)
+
+_TOK = re.compile(r"#W\d+|gift_card_\w+|\bgc_\w+|\b\d{8,}\b")
+
+
+def toks(*strings):
+    s = set()
+    for x in strings:
+        if x:
+            s |= set(_TOK.findall(x if isinstance(x, str) else json.dumps(x)))
+    return s
+
+
+def build_user(row, K):
+    calls = row["calls"]
+    fmt = lambda c: {"tool": c["name"], "arguments": c.get("arguments", {})}
+    return json.dumps({
+        "original_customer_message": row["query"],
+        "turn1_actions": [fmt(c) for c in calls[:K]],
+        "tail_actions_each_its_own_turn": [fmt(c) for c in calls[K:]],
+    }, ensure_ascii=False, indent=2)
+
+
+def validate(row, K, out):
+    calls = row["calls"]; tail = calls[K:]
+    if not isinstance(out, dict):
+        return "not a dict"
+    q1 = out.get("q1"); ack1 = out.get("ack1"); turns = out.get("turns")
+    if not isinstance(q1, str) or not q1.strip():
+        return "empty q1"
+    if not isinstance(ack1, str) or not ack1.strip():
+        return "empty ack1"
+    if not isinstance(turns, list) or len(turns) != len(tail):
+        return f"turns len {len(turns) if isinstance(turns,list) else '?'} != tail {len(tail)}"
+    texts = [q1, ack1]
+    for t in turns:
+        if not isinstance(t, dict) or not str(t.get("user", "")).strip() or not str(t.get("ack", "")).strip():
+            return "empty turn user/ack"
+        texts += [t["user"], t["ack"]]
+    for t in texts:
+        if "\u2014" in t or "\u2013" in t or " - " in t:
+            return "dash present"
+    allowed = toks(row["query"], *[c.get("arguments", {}) for c in calls])
+    new = toks(*texts) - allowed
+    if new:
+        return f"new ids {sorted(new)[:4]}"
+    tail_ids = (toks(*[c.get("arguments", {}) for c in tail])
+                - toks(*[c.get("arguments", {}) for c in calls[:K]]))
+    leak = toks(q1, ack1) & tail_ids
+    if leak:
+        return f"tail id leaked into q1/ack1 {sorted(leak)}"
+    return None
+
+
+def main():
+    rows = {json.loads(l)["example_id"]: json.loads(l)
+            for l in open(N100, encoding="utf-8") if l.strip()}
+    cand = []
+    for eid, r in rows.items():
+        md = r.get("metadata") or {}; ad = md.get("anchor_depth")
+        calls = r.get("calls") or []
+        if ad is None or ad < 2 or len(calls) <= ad + 1:
+            continue
+        cand.append(eid)
+    cand.sort()
+    print(f"candidates: {len(cand)}")
+
+    authored = {}
+    if AUTHORED.exists():
+        authored = json.loads(AUTHORED.read_text(encoding="utf-8"))
+    todo = [e for e in cand if e not in authored or authored[e].get("_err")]
+    print(f"already done: {len(cand)-len(todo)}   to author: {len(todo)}")
+
+    judge = make_judge(cfg["model"])
+    lock = threading.Lock(); done = [0]
+
+    def work(eid):
+        r = rows[eid]; K = r["metadata"]["anchor_depth"] + 1
+        user = build_user(r, K); last = None
+        for _ in range(3):
+            try:
+                out = judge.judge({"system": SYS, "user": user})
+            except Exception as e:  # noqa
+                last = f"api:{e}"; continue
+            err = validate(r, K, out)
+            if err is None:
+                rec = {"q1": out["q1"].strip(), "ack1": out["ack1"].strip(),
+                       "turns": [{"user": t["user"].strip(), "ack": t["ack"].strip()}
+                                 for t in out["turns"]]}
+                with lock:
+                    authored[eid] = rec; done[0] += 1
+                    if done[0] % 20 == 0:
+                        AUTHORED.write_text(json.dumps(authored, ensure_ascii=False, indent=1), encoding="utf-8")
+                        print(f"  ...{done[0]}/{len(todo)}")
+                return
+            last = err
+        with lock:
+            authored[eid] = {"_err": last or "unknown"}
+        print(f"  SKIP {eid}: {last}")
+
+    AUTHORED.parent.mkdir(parents=True, exist_ok=True)
+    with ThreadPoolExecutor(max_workers=WORKERS) as ex:
+        list(ex.map(work, todo))
+    AUTHORED.write_text(json.dumps(authored, ensure_ascii=False, indent=1), encoding="utf-8")
+
+    ok = sum(1 for e in cand if "q1" in authored.get(e, {}) and not authored.get(e, {}).get("_err"))
+    err = [e for e in cand if authored.get(e, {}).get("_err")]
+    print(f"\nauthored ok: {ok}/{len(cand)}   failed/skipped: {len(err)}")
+    for e in err[:15]:
+        print("  ", e, authored[e]["_err"])
+    print(f"wrote {AUTHORED.relative_to(ROOT)}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/unbundle/author_splits_v4.py b/tempscripts/story_remediation/unbundle/author_splits_v4.py
new file mode 100644
index 0000000000000000000000000000000000000000..b7d79ee219e15e10e8b874fe787108ca0379159d
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/author_splits_v4.py
@@ -0,0 +1,192 @@
+"""V4 authoring: humanize the split rows' dialogue to kill the two authorable C3
+tells found in v3 tail reasoning:
+  (a) "customer front-loads name+ZIP+order in one tidy sentence" -> too clean.
+  (b) "agent verified silently, never asked" -> no auth handshake.
+
+Fix is PROSE ONLY. The tool calls are never touched (guaranteed in the builder).
+q1 is now framed as the customer's REPLY to the agent asking them to verify their
+identity, so it opens with mild human disfluency and provides name/ZIP naturally
+rather than dumping everything up front. All user turns carry light, realistic
+friction. Everything else (past-tense own-turn acks, verbatim ids, no dashes) is
+unchanged from v2.
+
+Cache -> out/authored_v4.json  (idempotent). Run:
+  python -u temp/story_remediation/unbundle/author_splits_v4.py
+"""
+from __future__ import annotations
+import json, re, sys, threading, logging
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+import yaml
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+sys.path.insert(0, str(ROOT))
+for _n in ("azure", "azure.identity", "azure.core.pipeline.policies.http_logging_policy"):
+    logging.getLogger(_n).setLevel(logging.WARNING)
+from datasetreview.llm_client import make_judge  # noqa: E402
+
+N100 = ROOT / "distractor_generation_2" / "datasets" / "n100" / "trajectories.jsonl"
+AUTHORED = HERE / "out" / "authored_v4.json"
+cfg = yaml.safe_load(open(ROOT / "datasetreview" / "config.yaml", encoding="utf-8"))
+WORKERS = 8
+
+SYS = (
+ "You rewrite ONE retail customer-support conversation so it reads as a natural, "
+ "coherent multi-turn dialogue instead of a single giant request. It must make "
+ "perfect sense read start to finish, and above all it must sound like a REAL human "
+ "customer, not a tidy scripted prompt.\n\n"
+ "Framing of the opening: the agent has greeted the customer, the customer said they "
+ "need help, and the agent has just asked them to VERIFY their identity by giving "
+ "their name and ZIP code. So TURN 1 (q1) is the customer's REPLY to that request.\n\n"
+ "You are given the customer's original bundled message and the ordered backend "
+ "actions the agent took (tool name + arguments). The FIRST GROUP of actions "
+ "(authentication + lookups + the first real action) all happen in TURN 1. Each "
+ "remaining TAIL action becomes its own separate later turn, in order.\n\n"
+ "Return a JSON object EXACTLY like:\n"
+ '{ "q1": "<turn-1 customer message>", "ack1": "<agent reply AFTER turn 1>",\n'
+ '  "turns": [ {"user":"<customer message>","ack":"<agent reply AFTER doing it>"}, ... ] }\n\n'
+ "THE #1 RULE: An agent reply may ONLY confirm actions ALREADY performed. It must be "
+ "PAST TENSE and describe ONLY its own turn's action. NEVER let an agent say it did "
+ "something the customer has not yet asked for. Do not preview or promise a next step.\n"
+ "  - ack1 confirms ONLY the turn-1 actions. It must NOT mention any tail action.\n"
+ "  - Each turns[k].ack confirms ONLY that same turn's single action.\n\n"
+ "HUMANIZE (this is the new part, do it well):\n"
+ "A. q1 is a reply to 'can you verify your name and ZIP'. Start it the way a real "
+ "person answers: a small hesitation or filler is good ('Yeah, sure,', 'Oh, right,', "
+ "'Um, ok,', 'Sure thing,'), then give the name and ZIP, THEN say what they actually "
+ "want. Do NOT machine-list identifiers in one clinical sentence.\n"
+ "B. Give the customer mild, realistic friction across turns: slight informality, an "
+ "occasional 'I think', 'if that makes sense', 'sorry', a little context about WHY "
+ "they want it. Keep it believable, never over the top, never emoji.\n"
+ "C. Vary sentence shape and follow-up openers so no two turns feel stamped from a "
+ "template ('Thanks, one more thing', 'Ok so', 'Got it. Could you also', 'Perfect, "
+ "now', 'Oh and').\n\n"
+ "Hard rules:\n"
+ "1. q1 motivates ONLY the turn-1 actions. Do NOT mention or hint at any tail action.\n"
+ "2. Exactly one entry in \"turns\" per tail action, same order. Each \"user\" message "
+ "naturally triggers exactly that one action and nothing else.\n"
+ "3. The customer is ALREADY authenticated after turn 1. Later turns must NOT re-verify "
+ "identity or re-share name / ZIP / email / phone (unless an action's arguments are "
+ "about a DIFFERENT person, which is fine).\n"
+ "4. Do NOT re-request anything already done in an earlier turn.\n"
+ "5. Copy every identifier verbatim from the arguments: order ids (#W...), item / "
+ "product numbers, gift card ids, dollar amounts, exact quoted message or review text. "
+ "NEVER invent, drop, or alter an id.\n"
+ "6. Absolutely NO em dashes or en dashes. Use commas, periods, or parentheses.\n"
+ "Return ONLY the JSON object."
+)
+
+_TOK = re.compile(r"#W\d+|gift_card_\w+|\bgc_\w+|\b\d{8,}\b")
+
+
+def toks(*strings):
+    s = set()
+    for x in strings:
+        if x:
+            s |= set(_TOK.findall(x if isinstance(x, str) else json.dumps(x)))
+    return s
+
+
+def build_user(row, K):
+    calls = row["calls"]
+    fmt = lambda c: {"tool": c["name"], "arguments": c.get("arguments", {})}
+    return json.dumps({
+        "original_customer_message": row["query"],
+        "turn1_actions": [fmt(c) for c in calls[:K]],
+        "tail_actions_each_its_own_turn": [fmt(c) for c in calls[K:]],
+    }, ensure_ascii=False, indent=2)
+
+
+def validate(row, K, out):
+    calls = row["calls"]; tail = calls[K:]
+    if not isinstance(out, dict):
+        return "not a dict"
+    q1 = out.get("q1"); ack1 = out.get("ack1"); turns = out.get("turns")
+    if not isinstance(q1, str) or not q1.strip():
+        return "empty q1"
+    if not isinstance(ack1, str) or not ack1.strip():
+        return "empty ack1"
+    if not isinstance(turns, list) or len(turns) != len(tail):
+        return f"turns len {len(turns) if isinstance(turns,list) else '?'} != tail {len(tail)}"
+    texts = [q1, ack1]
+    for t in turns:
+        if not isinstance(t, dict) or not str(t.get("user", "")).strip() or not str(t.get("ack", "")).strip():
+            return "empty turn user/ack"
+        texts += [t["user"], t["ack"]]
+    for t in texts:
+        if "\u2014" in t or "\u2013" in t or " - " in t:
+            return "dash present"
+    allowed = toks(row["query"], *[c.get("arguments", {}) for c in calls])
+    new = toks(*texts) - allowed
+    if new:
+        return f"new ids {sorted(new)[:4]}"
+    tail_ids = (toks(*[c.get("arguments", {}) for c in tail])
+                - toks(*[c.get("arguments", {}) for c in calls[:K]]))
+    leak = toks(q1, ack1) & tail_ids
+    if leak:
+        return f"tail id leaked into q1/ack1 {sorted(leak)}"
+    return None
+
+
+def main():
+    rows = {json.loads(l)["example_id"]: json.loads(l)
+            for l in open(N100, encoding="utf-8") if l.strip()}
+    cand = []
+    for eid, r in rows.items():
+        md = r.get("metadata") or {}; ad = md.get("anchor_depth")
+        calls = r.get("calls") or []
+        if ad is None or ad < 2 or len(calls) <= ad + 1:
+            continue
+        cand.append(eid)
+    cand.sort()
+    print(f"candidates: {len(cand)}")
+
+    authored = {}
+    if AUTHORED.exists():
+        authored = json.loads(AUTHORED.read_text(encoding="utf-8"))
+    todo = [e for e in cand if e not in authored or authored[e].get("_err")]
+    print(f"already done: {len(cand)-len(todo)}   to author: {len(todo)}")
+
+    judge = make_judge(cfg["model"])
+    lock = threading.Lock(); done = [0]
+
+    def work(eid):
+        r = rows[eid]; K = r["metadata"]["anchor_depth"] + 1
+        user = build_user(r, K); last = None
+        for _ in range(3):
+            try:
+                out = judge.judge({"system": SYS, "user": user})
+            except Exception as e:  # noqa
+                last = f"api:{e}"; continue
+            err = validate(r, K, out)
+            if err is None:
+                rec = {"q1": out["q1"].strip(), "ack1": out["ack1"].strip(),
+                       "turns": [{"user": t["user"].strip(), "ack": t["ack"].strip()}
+                                 for t in out["turns"]]}
+                with lock:
+                    authored[eid] = rec; done[0] += 1
+                    if done[0] % 20 == 0:
+                        AUTHORED.write_text(json.dumps(authored, ensure_ascii=False, indent=1), encoding="utf-8")
+                        print(f"  ...{done[0]}/{len(todo)}")
+                return
+            last = err
+        with lock:
+            authored[eid] = {"_err": last or "unknown"}
+        print(f"  SKIP {eid}: {last}")
+
+    AUTHORED.parent.mkdir(parents=True, exist_ok=True)
+    with ThreadPoolExecutor(max_workers=WORKERS) as ex:
+        list(ex.map(work, todo))
+    AUTHORED.write_text(json.dumps(authored, ensure_ascii=False, indent=1), encoding="utf-8")
+
+    ok = sum(1 for e in cand if "q1" in authored.get(e, {}) and not authored.get(e, {}).get("_err"))
+    err = [e for e in cand if authored.get(e, {}).get("_err")]
+    print(f"\nauthored ok: {ok}/{len(cand)}   failed/skipped: {len(err)}")
+    for e in err[:15]:
+        print("  ", e, authored[e]["_err"])
+    print(f"wrote {AUTHORED.relative_to(ROOT)}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/unbundle/build_all.py b/tempscripts/story_remediation/unbundle/build_all.py
new file mode 100644
index 0000000000000000000000000000000000000000..3fb4d081604de63fdaae9842fe70024c738eb9a4
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/build_all.py
@@ -0,0 +1,139 @@
+"""Full unbundle build: split every authored candidate's single bundled turn
+into T1 (prefix + F, the preserved trie divergence) plus ONE later turn per
+tail call (one action per turn, matching real tau2 and the prototype finding
+that multi-call tail turns get caught 6/6 vs single-call 1/4).
+
+Base = original n100 (795 rows). Each authored candidate row is REPLACED by its
+split rows; all other rows (non-candidates + any skipped candidate) pass through
+unchanged. Writes out/trajectories_all.jsonl.
+
+History chaining per tail turn i (0-based, i in 0..N-1):
+  orig_history
+  + user(q1)
+  + assistant(tool_calls = prefix+F)          + tool msgs (verbatim outputs)
+  + assistant(turns[0].bridge)                 # confirms turn 1
+  + for j in 0..i-1:
+        user(turns[j].user)
+        assistant(tool_calls=[tail[j]]) + tool msg
+        assistant(turns[j+1].bridge)           # confirms tail[j]
+  -> current row: query=turns[i].user, calls=[tail[i]]
+
+Auth lives in the prefix (anchor_depth>=2), so tail turns never re-auth.
+Run: python -u temp/story_remediation/unbundle/build_all.py
+"""
+from __future__ import annotations
+import json, copy
+from pathlib import Path
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+N100 = ROOT / "distractor_generation_2" / "datasets" / "n100" / "trajectories.jsonl"
+AUTHORED = HERE / "out" / "authored.json"
+OUT = HERE / "out" / "trajectories_all.jsonl"
+
+AUTH_TOOLS = {"find_user_id_by_name_zip", "find_user_id_by_email",
+              "find_user_id_by_phone", "authenticate", "find_user"}
+
+
+def hist_of(r):
+    return r.get("history") or (r.get("metadata") or {}).get("history") or []
+
+
+def umsg(content):
+    return {"role": "user", "content": content, "tool_calls": [], "tool_call_id": None}
+
+
+def amsg(content=None, tool_calls=None):
+    return {"role": "assistant", "content": content,
+            "tool_calls": copy.deepcopy(tool_calls) if tool_calls else [],
+            "tool_call_id": None}
+
+
+def tmsg(call):
+    return {"role": "tool", "content": call.get("output"),
+            "tool_calls": [], "tool_call_id": None}
+
+
+def main():
+    rows = [json.loads(l) for l in open(N100, encoding="utf-8") if l.strip()]
+    by_eid = {r["example_id"]: r for r in rows}
+    authored = json.loads(AUTHORED.read_text(encoding="utf-8"))
+    ok = {e: a for e, a in authored.items() if "q1" in a and not a.get("_err")}
+    print(f"authored ok: {len(ok)}   skipped: {len(authored)-len(ok)}")
+
+    out = []
+    split_eids = set()
+    reauth_flags = []
+    for r in rows:
+        eid = r["example_id"]
+        if eid not in ok:
+            out.append(r)            # non-candidate or skipped -> unchanged
+            continue
+        sp = ok[eid]
+        md = r["metadata"]; ad = md["anchor_depth"]
+        calls = r["calls"]
+        prefixF = calls[:ad + 1]
+        tail = calls[ad + 1:]
+        assert len(tail) == len(sp["turns"]), f"{eid}: tail {len(tail)} != turns {len(sp['turns'])}"
+        orig_hist = hist_of(r)
+        split_eids.add(eid)
+
+        # ---- T1: preserved trie divergence (prefix + F) ----
+        t1 = copy.deepcopy(r)
+        t1["query"] = sp["q1"]
+        t1["calls"] = copy.deepcopy(prefixF)
+        t1["history"] = copy.deepcopy(orig_hist)
+        t1["metadata"] = copy.deepcopy(md)
+        t1["metadata"]["history"] = copy.deepcopy(orig_hist)
+        t1["metadata"]["unbundle_role"] = "turn1"
+        t1["metadata"]["orig_eid"] = eid
+        out.append(t1)
+
+        # ---- running history: turn1 shown as completed ----
+        base_hist = (copy.deepcopy(orig_hist)
+                     + [umsg(sp["q1"]), amsg(tool_calls=prefixF)]
+                     + [tmsg(c) for c in prefixF]
+                     + [amsg(content=sp["turns"][0]["bridge"])])
+
+        run_hist = base_hist
+        for i, call in enumerate(tail):
+            if call["name"] in AUTH_TOOLS:
+                reauth_flags.append((eid, i, call["name"]))
+            trow = copy.deepcopy(r)
+            trow["example_id"] = f"{eid}-t{i + 2}"
+            trow["query"] = sp["turns"][i]["user"]
+            trow["calls"] = [copy.deepcopy(call)]
+            trow["history"] = copy.deepcopy(run_hist)
+            trow["metadata"] = copy.deepcopy(md)
+            trow["metadata"]["history"] = copy.deepcopy(run_hist)
+            trow["metadata"]["unbundle_role"] = f"turn{i + 2}"
+            trow["metadata"]["orig_eid"] = eid
+            out.append(trow)
+            # advance history: this tail turn completed + next bridge (if any)
+            run_hist = (copy.deepcopy(run_hist)
+                        + [umsg(sp["turns"][i]["user"]), amsg(tool_calls=[call]), tmsg(call)])
+            if i + 1 < len(tail):
+                run_hist = run_hist + [amsg(content=sp["turns"][i + 1]["bridge"])]
+
+    OUT.parent.mkdir(parents=True, exist_ok=True)
+    with OUT.open("w", encoding="utf-8") as fh:
+        for r in out:
+            fh.write(json.dumps(r, ensure_ascii=False) + "\n")
+
+    n_tail = sum(1 for r in out if str((r.get("metadata") or {}).get("unbundle_role", "")).startswith("turn")
+                 and (r.get("metadata") or {}).get("unbundle_role") != "turn1"
+                 and (r.get("metadata") or {}).get("orig_eid"))
+    print(f"input rows: {len(rows)}   output rows: {len(out)}")
+    print(f"split candidates: {len(split_eids)}   T1 rows: {len(split_eids)}   tail rows: {n_tail}")
+    print(f"unchanged rows: {len(rows) - len(split_eids)}")
+    if reauth_flags:
+        print(f"WARNING: {len(reauth_flags)} tail turns contain an auth tool:")
+        for f in reauth_flags[:10]:
+            print("   ", f)
+    else:
+        print("no tail turn re-authenticates (good)")
+    print(f"wrote {OUT.relative_to(ROOT)}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/unbundle/build_all_v2.py b/tempscripts/story_remediation/unbundle/build_all_v2.py
new file mode 100644
index 0000000000000000000000000000000000000000..55cd7af5c27e25d007fb6675700553a77a267856
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/build_all_v2.py
@@ -0,0 +1,116 @@
+"""V2 build: same structural split, but corrected acknowledgement ordering.
+
+Every completed turn is rendered in history as:  user request -> tool call(s)
+-> PAST-TENSE ack of that same turn. An ack never precedes its own request, so
+the v1 "I've already done the thing you're about to ask" contradiction is gone.
+
+History for tail turn i (0-based, maps to tail call i):
+  orig_history
+  + user(q1) + assistant(tool_calls=prefix+F) + tool msgs + assistant(ack1)
+  + for j in 0..i-1:
+        user(turns[j].user) + assistant(tool_calls=[tail[j]]) + tool msg
+        + assistant(turns[j].ack)
+  -> current row: query=turns[i].user, calls=[tail[i]]  (its ack shown only in later rows)
+
+Reads out/authored_v2.json, writes out/trajectories_all_v2.jsonl.
+Run: python -u temp/story_remediation/unbundle/build_all_v2.py
+"""
+from __future__ import annotations
+import json, copy
+from pathlib import Path
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+N100 = ROOT / "distractor_generation_2" / "datasets" / "n100" / "trajectories.jsonl"
+AUTHORED = HERE / "out" / "authored_v2.json"
+OUT = HERE / "out" / "trajectories_all_v2.jsonl"
+AUTH_TOOLS = {"find_user_id_by_name_zip", "find_user_id_by_email",
+              "find_user_id_by_phone", "authenticate", "find_user"}
+
+
+def hist_of(r):
+    return r.get("history") or (r.get("metadata") or {}).get("history") or []
+
+
+def umsg(c):
+    return {"role": "user", "content": c, "tool_calls": [], "tool_call_id": None}
+
+
+def amsg(content=None, tool_calls=None):
+    return {"role": "assistant", "content": content,
+            "tool_calls": copy.deepcopy(tool_calls) if tool_calls else [],
+            "tool_call_id": None}
+
+
+def tmsg(call):
+    return {"role": "tool", "content": call.get("output"), "tool_calls": [], "tool_call_id": None}
+
+
+def main():
+    rows = [json.loads(l) for l in open(N100, encoding="utf-8") if l.strip()]
+    authored = json.loads(AUTHORED.read_text(encoding="utf-8"))
+    ok = {e: a for e, a in authored.items() if "q1" in a and not a.get("_err")}
+    print(f"authored ok: {len(ok)}   skipped: {len(authored)-len(ok)}")
+
+    out = []; split_eids = set(); reauth = []
+    for r in rows:
+        eid = r["example_id"]
+        if eid not in ok:
+            out.append(r); continue
+        sp = ok[eid]; md = r["metadata"]; ad = md["anchor_depth"]
+        calls = r["calls"]; prefixF = calls[:ad + 1]; tail = calls[ad + 1:]
+        assert len(tail) == len(sp["turns"]), f"{eid}: tail {len(tail)} != turns {len(sp['turns'])}"
+        orig_hist = hist_of(r); split_eids.add(eid)
+
+        # T1: preserved trie divergence (query narrowed to prefix+F)
+        t1 = copy.deepcopy(r)
+        t1["query"] = sp["q1"]; t1["calls"] = copy.deepcopy(prefixF)
+        t1["history"] = copy.deepcopy(orig_hist)
+        t1["metadata"] = copy.deepcopy(md)
+        t1["metadata"]["history"] = copy.deepcopy(orig_hist)
+        t1["metadata"]["unbundle_role"] = "turn1"; t1["metadata"]["orig_eid"] = eid
+        out.append(t1)
+
+        # turn-1 completed block (with its OWN past-tense ack1)
+        base_hist = (copy.deepcopy(orig_hist)
+                     + [umsg(sp["q1"]), amsg(tool_calls=prefixF)]
+                     + [tmsg(c) for c in prefixF]
+                     + [amsg(content=sp["ack1"])])
+
+        for i, call in enumerate(tail):
+            if call["name"] in AUTH_TOOLS:
+                reauth.append((eid, i, call["name"]))
+            # history = base + completed tail turns 0..i-1 (each with its own ack)
+            hist = copy.deepcopy(base_hist)
+            for j in range(i):
+                cj = tail[j]
+                hist += [umsg(sp["turns"][j]["user"]), amsg(tool_calls=[cj]),
+                         tmsg(cj), amsg(content=sp["turns"][j]["ack"])]
+            trow = copy.deepcopy(r)
+            trow["example_id"] = f"{eid}-t{i + 2}"
+            trow["query"] = sp["turns"][i]["user"]
+            trow["calls"] = [copy.deepcopy(call)]
+            trow["history"] = hist
+            trow["metadata"] = copy.deepcopy(md)
+            trow["metadata"]["history"] = copy.deepcopy(hist)
+            trow["metadata"]["unbundle_role"] = f"turn{i + 2}"
+            trow["metadata"]["orig_eid"] = eid
+            out.append(trow)
+
+    OUT.parent.mkdir(parents=True, exist_ok=True)
+    with OUT.open("w", encoding="utf-8") as fh:
+        for r in out:
+            fh.write(json.dumps(r, ensure_ascii=False) + "\n")
+
+    n_tail = sum(1 for r in out
+                 if (r.get("metadata") or {}).get("orig_eid")
+                 and (r.get("metadata") or {}).get("unbundle_role") not in (None, "turn1"))
+    print(f"input rows: {len(rows)}   output rows: {len(out)}")
+    print(f"split candidates: {len(split_eids)}   T1: {len(split_eids)}   tail: {n_tail}")
+    print(f"unchanged rows: {len(rows) - len(split_eids)}")
+    print("re-auth in tail (verify DIFFERENT person):", len(reauth), reauth[:6])
+    print(f"wrote {OUT.relative_to(ROOT)}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/unbundle/build_all_v3.py b/tempscripts/story_remediation/unbundle/build_all_v3.py
new file mode 100644
index 0000000000000000000000000000000000000000..b63b1f598226ca031ab72d982f1d93f94f03b2be
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/build_all_v3.py
@@ -0,0 +1,204 @@
+"""V3 build: remove the residual tells that live in the INHERITED base history.
+
+Diagnosis (from C3 reasoning on still-caught v2 tails): the original n100
+"humanized" pre-history front-loads future/tail intents ("a return to handle",
+"a receipt without prices") and restates identity ("Hi, this is Mona Frey")
+right before q1. Both read as scripted-from-a-template.
+
+Fix (reuses v2 authored q1/ack1/turns unchanged):
+  * 259 candidates whose pre-history has NO tool calls  -> replace the whole
+    teaser with just the greeting. q1 (which already carries name+ZIP) becomes
+    the true first user turn, so the front-loading AND the duplicate identity
+    both disappear.
+  * 23 candidates whose pre-history DOES auth (find_user[/get_user]) -> rebuild
+    a clean minimal auth exchange that keeps those exact tool calls but drops
+    the front-loading teaser and any duplicative post-auth actions. Identity is
+    given once, with no intent preview.
+
+Everything downstream (T1 = prefix+F, tail = one action per turn, past-tense
+acks) is identical to v2. Reads out/authored_v2.json, writes
+out/trajectories_all_v3.jsonl.
+Run: python -u temp/story_remediation/unbundle/build_all_v3.py
+"""
+from __future__ import annotations
+import json, copy, hashlib, re
+from pathlib import Path
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+N100 = ROOT / "distractor_generation_2" / "datasets" / "n100" / "trajectories.jsonl"
+AUTHORED = HERE / "out" / "authored_v2.json"
+Q1FIX = HERE / "out" / "authored_q1fix_v3.json"
+OUT = HERE / "out" / "trajectories_all_v3.jsonl"
+
+AUTH_LEAD = ("find_user_id_by_name_zip", "get_user_details")
+AUTH_TOOLS = {"find_user_id_by_name_zip", "find_user_id_by_email",
+              "find_user_id_by_phone", "authenticate", "find_user"}
+
+OPENERS = [
+    "Hi, I need a hand with my account. I'm {first} {last}, ZIP {zip}.",
+    "Hello, could you pull up my account? Name is {first} {last}, ZIP {zip}.",
+    "Hi there, I need some help on my account. I'm {first} {last}, ZIP {zip}.",
+    "Hey, can you access my account? Name's {first} {last}, ZIP {zip}.",
+]
+VERIFIED = [
+    "Thanks {first}, you're verified. What can I do for you?",
+    "Great {first}, I've pulled up your account. How can I help?",
+    "You're all set {first}. What would you like to do?",
+    "Verified, thanks {first}. What can I help with?",
+]
+
+
+def hist_of(r):
+    return r.get("history") or (r.get("metadata") or {}).get("history") or []
+
+
+def umsg(c):
+    return {"role": "user", "content": c, "tool_calls": [], "tool_call_id": None}
+
+
+def amsg(content=None, tool_calls=None):
+    return {"role": "assistant", "content": content,
+            "tool_calls": copy.deepcopy(tool_calls) if tool_calls else [],
+            "tool_call_id": None}
+
+
+def tmsg(call):
+    return {"role": "tool", "content": call.get("output"), "tool_calls": [], "tool_call_id": None}
+
+
+def pick(lst, eid):
+    return lst[int(hashlib.md5(eid.encode()).hexdigest(), 16) % len(lst)]
+
+
+def greeting_of(r):
+    h = hist_of(r)
+    if h and h[0].get("role") == "assistant" and not h[0].get("tool_calls") and h[0].get("content"):
+        return copy.deepcopy(h[0])
+    return amsg(content="Hi! How can I help you today?")
+
+
+def clean_prehistory(r):
+    """Return (cleaned_history, had_auth). For the 23 auth-in-history rows keep a
+    minimal auth exchange around the real find_user/get_user calls; else greeting."""
+    h = hist_of(r); eid = r["example_id"]
+    greet = greeting_of(r)
+    # gather the LEADING auth calls actually present in the pre-history, in order
+    lead = []
+    for m in h:
+        for t in (m.get("tool_calls") or []):
+            if t["name"] in AUTH_LEAD:
+                lead.append(copy.deepcopy(t))
+    # only keep the contiguous leading auth calls (find_user then optional get_user)
+    kept = []
+    for t in lead:
+        if not kept and t["name"] == "find_user_id_by_name_zip":
+            kept.append(t)
+        elif kept and t["name"] == "get_user_details":
+            kept.append(t); break
+        else:
+            break
+    if not kept:
+        return [greet], False
+    args = kept[0].get("arguments", {})
+    first = args.get("first_name", ""); last = args.get("last_name", ""); zp = args.get("zip", "")
+    opener = pick(OPENERS, eid).format(first=first, last=last, zip=zp)
+    verified = pick(VERIFIED, eid).format(first=first or "there")
+    hist = [greet, umsg(opener)]
+    for t in kept:
+        hist += [amsg(tool_calls=[t]), tmsg(t)]
+    hist += [amsg(content=verified)]
+    return hist, True
+
+
+def main():
+    rows = [json.loads(l) for l in open(N100, encoding="utf-8") if l.strip()]
+    authored = json.loads(AUTHORED.read_text(encoding="utf-8"))
+    q1fix = json.loads(Q1FIX.read_text(encoding="utf-8")) if Q1FIX.exists() else {}
+    ok = {e: a for e, a in authored.items() if "q1" in a and not a.get("_err")}
+    print(f"authored ok: {len(ok)}   skipped: {len(authored)-len(ok)}   q1-overrides: {len(q1fix)}")
+
+    out = []; split_eids = set(); n_auth = 0; ident_leak = []
+    for r in rows:
+        eid = r["example_id"]
+        if eid not in ok:
+            out.append(r); continue
+        sp = copy.deepcopy(ok[eid]); md = r["metadata"]; ad = md["anchor_depth"]
+        if eid in q1fix:                      # cleaned already-verified q1
+            sp["q1"] = q1fix[eid]["q1"]
+        calls = r["calls"]; prefixF = calls[:ad + 1]; tail = calls[ad + 1:]
+        assert len(tail) == len(sp["turns"]), f"{eid}: tail {len(tail)} != turns {len(sp['turns'])}"
+        base_prehist, had_auth = clean_prehistory(r)
+        n_auth += int(had_auth); split_eids.add(eid)
+
+        # for auth-in-history rows, q1 must NOT re-introduce the person (full name
+        # or a self-intro like "I'm Reid"); a name inside an id (gc_reid_22) is fine
+        if had_auth:
+            fu = next((t for m in hist_of(r) for t in (m.get("tool_calls") or [])
+                       if t["name"] == "find_user_id_by_name_zip"), None)
+            a = (fu or {}).get("arguments", {})
+            first = str(a.get("first_name", "")); last = str(a.get("last_name", ""))
+            q1l = sp["q1"].lower()
+            pats = []
+            if first and last:
+                pats.append(re.escape(f"{first} {last}".lower()))
+            if first and len(first) >= 3:
+                pats.append(r"\b(i'?m|i am|this is|name is|it'?s)\s+" + re.escape(first.lower()))
+            if pats and re.search("|".join(pats), q1l):
+                ident_leak.append((eid, first))
+
+        # T1: preserved trie divergence
+        t1 = copy.deepcopy(r)
+        t1["query"] = sp["q1"]; t1["calls"] = copy.deepcopy(prefixF)
+        t1["history"] = copy.deepcopy(base_prehist)
+        t1["metadata"] = copy.deepcopy(md)
+        t1["metadata"]["history"] = copy.deepcopy(base_prehist)
+        t1["metadata"]["unbundle_role"] = "turn1"; t1["metadata"]["orig_eid"] = eid
+        out.append(t1)
+
+        # turn-1 completed block (own past-tense ack1)
+        base_hist = (copy.deepcopy(base_prehist)
+                     + [umsg(sp["q1"]), amsg(tool_calls=prefixF)]
+                     + [tmsg(c) for c in prefixF]
+                     + [amsg(content=sp["ack1"])])
+
+        for i, call in enumerate(tail):
+            hist = copy.deepcopy(base_hist)
+            for j in range(i):
+                cj = tail[j]
+                hist += [umsg(sp["turns"][j]["user"]), amsg(tool_calls=[cj]),
+                         tmsg(cj), amsg(content=sp["turns"][j]["ack"])]
+            trow = copy.deepcopy(r)
+            trow["example_id"] = f"{eid}-t{i + 2}"
+            trow["query"] = sp["turns"][i]["user"]
+            trow["calls"] = [copy.deepcopy(call)]
+            trow["history"] = hist
+            trow["metadata"] = copy.deepcopy(md)
+            trow["metadata"]["history"] = copy.deepcopy(hist)
+            trow["metadata"]["unbundle_role"] = f"turn{i + 2}"
+            trow["metadata"]["orig_eid"] = eid
+            out.append(trow)
+
+    OUT.parent.mkdir(parents=True, exist_ok=True)
+    with OUT.open("w", encoding="utf-8") as fh:
+        for r in out:
+            fh.write(json.dumps(r, ensure_ascii=False) + "\n")
+
+    n_tail = sum(1 for r in out
+                 if (r.get("metadata") or {}).get("orig_eid")
+                 and (r.get("metadata") or {}).get("unbundle_role") not in (None, "turn1"))
+    print(f"input rows: {len(rows)}   output rows: {len(out)}")
+    print(f"split: {len(split_eids)}   greeting-only(259-type): {len(split_eids)-n_auth}   "
+          f"auth-in-history(23-type): {n_auth}")
+    print(f"tail rows: {n_tail}   unchanged: {len(rows)-len(split_eids)}")
+    if ident_leak:
+        print(f"WARNING q1 restates identity already in cleaned history ({len(ident_leak)}):")
+        for x in ident_leak:
+            print("   ", x)
+    else:
+        print("no q1 restates cleaned-history identity (good)")
+    print(f"wrote {OUT.relative_to(ROOT)}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/unbundle/build_all_v4.py b/tempscripts/story_remediation/unbundle/build_all_v4.py
new file mode 100644
index 0000000000000000000000000000000000000000..6dc7a68d2f8421842d708df0b0354740c5f0014b
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/build_all_v4.py
@@ -0,0 +1,243 @@
+"""V4 build: add a real auth handshake (agent asks -> customer provides) and use the
+humanized v4 dialogue, WITHOUT touching a single tool call.
+
+Structural change vs v3 is PROSE ONLY:
+  * greeting-only rows (259): base history becomes
+        [greeting] [user: vague opener, no identifiers] [agent: please verify name+ZIP]
+    and the T1 user turn (q1) is the customer's reply that provides name/ZIP and the
+    first task. The T1 tool calls (auth + F) are IDENTICAL to v3 and stay in one turn.
+  * auth-in-history rows (23): the pre-history auth exchange is rebuilt as a handshake
+    [greeting] [user: vague opener] [agent: verify?] [user: name+ZIP] [auth calls]
+    [agent: verified]. Same find_user/get_user calls as v3, kept verbatim. q1 stays the
+    v3 clean task-only message (no identity restated).
+
+INVARIANT: for every example_id, this build asserts row["calls"] is byte-identical to
+v3's row["calls"]. If any call differs the build aborts. The trie is therefore
+unchanged and every confuser still rivals its real node at the same cutoff.
+
+Reads out/authored_v4.json (+ v2/q1fix for fallbacks), writes
+out/trajectories_all_v4.jsonl. Run:
+  python -u temp/story_remediation/unbundle/build_all_v4.py
+"""
+from __future__ import annotations
+import json, copy, hashlib, re
+from pathlib import Path
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+N100 = ROOT / "distractor_generation_2" / "datasets" / "n100" / "trajectories.jsonl"
+AUTHORED4 = HERE / "out" / "authored_v4.json"
+AUTHORED2 = HERE / "out" / "authored_v2.json"
+Q1FIX = HERE / "out" / "authored_q1fix_v3.json"
+V3 = HERE / "out" / "trajectories_all_v3.jsonl"
+OUT = HERE / "out" / "trajectories_all_v4.jsonl"
+
+AUTH_LEAD = ("find_user_id_by_name_zip", "get_user_details")
+
+# vague openers: NO name / ZIP / email / order id (identity comes only after the ask)
+OPENERS_VAGUE = [
+    "Hi, I need a hand with something on my account.",
+    "Hello, I'm hoping you can help me with one of my orders.",
+    "Hey there, I've got a question about my account.",
+    "Hi, could you help me sort something out on my account?",
+    "Hello, I need to take care of a couple of things on my order.",
+    "Hi, I was hoping to get some help with my account today.",
+    "Hey, I need help with something. Not sure who to ask.",
+    "Hi there, can you help me with an order issue?",
+]
+# agent asks to verify identity (name + ZIP)
+VERIFY_ASK = [
+    "Of course, I'd be glad to help. First, can I verify your identity? Could you give me your full name and ZIP code?",
+    "Happy to help with that. Before I pull anything up, could you confirm your name and ZIP code for me?",
+    "Sure thing. To access your account I'll need to verify you first. What's your full name and ZIP code?",
+    "I can help with that. For security, could you share your full name and the ZIP code on your account?",
+    "Absolutely. Let me just verify you first. Can I get your name and ZIP code, please?",
+    "Glad to help. To start, could you confirm your full name and ZIP code so I can find your account?",
+]
+# for the 23 auth-in-history rows: the customer provides identity (mild disfluency)
+ID_PROVIDE = [
+    "Yeah, sure. It's {first} {last}, and the ZIP is {zip}.",
+    "Oh, right. {first} {last}, ZIP {zip}.",
+    "Of course, it's {first} {last}. ZIP code's {zip}.",
+    "Sure thing. Name's {first} {last}, and my ZIP is {zip}.",
+    "Um, ok. {first} {last}, and the ZIP on the account is {zip}.",
+]
+VERIFIED = [
+    "Thanks {first}, you're all verified. What can I do for you?",
+    "Great, I've got your account pulled up, {first}. How can I help?",
+    "You're all set, {first}. What would you like to do?",
+    "Perfect, verified. Thanks {first}. What can I help with?",
+]
+
+
+def hist_of(r):
+    return r.get("history") or (r.get("metadata") or {}).get("history") or []
+
+
+def umsg(c):
+    return {"role": "user", "content": c, "tool_calls": [], "tool_call_id": None}
+
+
+def amsg(content=None, tool_calls=None):
+    return {"role": "assistant", "content": content,
+            "tool_calls": copy.deepcopy(tool_calls) if tool_calls else [],
+            "tool_call_id": None}
+
+
+def tmsg(call):
+    return {"role": "tool", "content": call.get("output"), "tool_calls": [], "tool_call_id": None}
+
+
+def pick(lst, eid, salt=""):
+    return lst[int(hashlib.md5((salt + eid).encode()).hexdigest(), 16) % len(lst)]
+
+
+def greeting_of(r):
+    h = hist_of(r)
+    if h and h[0].get("role") == "assistant" and not h[0].get("tool_calls") and h[0].get("content"):
+        return copy.deepcopy(h[0])
+    return amsg(content="Hi! How can I help you today?")
+
+
+def leading_auth(r):
+    lead = []
+    for m in hist_of(r):
+        for t in (m.get("tool_calls") or []):
+            if t["name"] in AUTH_LEAD:
+                lead.append(copy.deepcopy(t))
+    kept = []
+    for t in lead:
+        if not kept and t["name"] == "find_user_id_by_name_zip":
+            kept.append(t)
+        elif kept and t["name"] == "get_user_details":
+            kept.append(t); break
+        else:
+            break
+    return kept
+
+
+def base_history(r):
+    """(cleaned_history, had_auth). Prose-only handshake; no call added or removed
+    beyond the exact leading auth calls that already exist in v3's pre-history."""
+    eid = r["example_id"]
+    greet = greeting_of(r)
+    opener = umsg(pick(OPENERS_VAGUE, eid, "op"))
+    ask = amsg(content=pick(VERIFY_ASK, eid, "ask"))
+    kept = leading_auth(r)
+    if not kept:
+        # greeting-only row: handshake is greeting -> opener -> ask; q1 (the T1 turn)
+        # is the customer's reply that supplies name/ZIP and the first task.
+        return [greet, opener, ask], False
+    # auth-in-history row: full handshake around the real auth calls.
+    a = kept[0].get("arguments", {})
+    first = a.get("first_name", ""); last = a.get("last_name", ""); zp = a.get("zip", "")
+    idp = umsg(pick(ID_PROVIDE, eid, "idp").format(first=first, last=last, zip=zp))
+    verified = amsg(content=pick(VERIFIED, eid, "ok").format(first=first or "there"))
+    hist = [greet, opener, ask, idp]
+    for t in kept:
+        hist += [amsg(tool_calls=[t]), tmsg(t)]
+    hist += [verified]
+    return hist, True
+
+
+def calls_sig(calls):
+    return [(c.get("name"), json.dumps(c.get("arguments", {}), sort_keys=True, ensure_ascii=False))
+            for c in (calls or [])]
+
+
+def main():
+    rows = [json.loads(l) for l in open(N100, encoding="utf-8") if l.strip()]
+    a4 = json.loads(AUTHORED4.read_text(encoding="utf-8"))
+    a2 = json.loads(AUTHORED2.read_text(encoding="utf-8"))
+    q1fix = json.loads(Q1FIX.read_text(encoding="utf-8")) if Q1FIX.exists() else {}
+    v3 = {json.loads(l)["example_id"]: json.loads(l)
+          for l in open(V3, encoding="utf-8") if l.strip()}
+    # split EXACTLY the confusers v3 split, so the only delta vs v3 is prose.
+    v3_split = {r["metadata"]["orig_eid"] for r in v3.values()
+                if (r.get("metadata") or {}).get("unbundle_role") == "turn1"}
+
+    def bundle(eid):
+        b = a4.get(eid)
+        if b and "q1" in b and not b.get("_err"):
+            return b
+        b = a2.get(eid)                              # fall back to v2 text if v4 failed
+        if b and "q1" in b and not b.get("_err"):
+            return b
+        return None
+
+    ok = {e: bundle(e) for e in a4 if bundle(e)}
+    for e in a2:                                     # include any v2-only successes
+        if e not in ok and bundle(e):
+            ok[e] = bundle(e)
+    print(f"usable bundles: {len(ok)}   (v4 primary, v2 fallback)")
+
+    out = []; split_eids = set(); n_auth = 0
+    for r in rows:
+        eid = r["example_id"]
+        if eid not in ok or eid not in v3_split:
+            out.append(r); continue
+        sp = copy.deepcopy(ok[eid]); md = r["metadata"]; ad = md["anchor_depth"]
+        calls = r["calls"]; prefixF = calls[:ad + 1]; tail = calls[ad + 1:]
+        if len(tail) != len(sp["turns"]):
+            out.append(r); continue                  # schema mismatch -> leave original
+        base_prehist, had_auth = base_history(r)
+        if had_auth and eid in q1fix:                # 23-type: keep clean task-only q1
+            sp["q1"] = q1fix[eid]["q1"]
+        n_auth += int(had_auth); split_eids.add(eid)
+
+        t1 = copy.deepcopy(r)
+        t1["query"] = sp["q1"]; t1["calls"] = copy.deepcopy(prefixF)
+        t1["history"] = copy.deepcopy(base_prehist)
+        t1["metadata"] = copy.deepcopy(md)
+        t1["metadata"]["history"] = copy.deepcopy(base_prehist)
+        t1["metadata"]["unbundle_role"] = "turn1"; t1["metadata"]["orig_eid"] = eid
+        out.append(t1)
+
+        base_hist = (copy.deepcopy(base_prehist)
+                     + [umsg(sp["q1"]), amsg(tool_calls=prefixF)]
+                     + [tmsg(c) for c in prefixF]
+                     + [amsg(content=sp["ack1"])])
+        for i, call in enumerate(tail):
+            hist = copy.deepcopy(base_hist)
+            for j in range(i):
+                cj = tail[j]
+                hist += [umsg(sp["turns"][j]["user"]), amsg(tool_calls=[cj]),
+                         tmsg(cj), amsg(content=sp["turns"][j]["ack"])]
+            trow = copy.deepcopy(r)
+            trow["example_id"] = f"{eid}-t{i + 2}"
+            trow["query"] = sp["turns"][i]["user"]
+            trow["calls"] = [copy.deepcopy(call)]
+            trow["history"] = hist
+            trow["metadata"] = copy.deepcopy(md)
+            trow["metadata"]["history"] = copy.deepcopy(hist)
+            trow["metadata"]["unbundle_role"] = f"turn{i + 2}"
+            trow["metadata"]["orig_eid"] = eid
+            out.append(trow)
+
+    # HARD INVARIANT: calls identical to v3 for every row (trie untouched).
+    v4 = {r["example_id"]: r for r in out}
+    assert set(v4) == set(v3), (
+        f"row-id set changed vs v3: +{sorted(set(v4)-set(v3))[:3]} "
+        f"-{sorted(set(v3)-set(v4))[:3]}")
+    bad = [eid for eid in v3 if calls_sig(v3[eid]["calls"]) != calls_sig(v4[eid]["calls"])]
+    assert not bad, f"CALLS CHANGED vs v3 for {len(bad)} rows, e.g. {bad[:5]}"
+
+    OUT.parent.mkdir(parents=True, exist_ok=True)
+    with OUT.open("w", encoding="utf-8") as fh:
+        for r in out:
+            fh.write(json.dumps(r, ensure_ascii=False) + "\n")
+
+    n_tail = sum(1 for r in out
+                 if (r.get("metadata") or {}).get("orig_eid")
+                 and (r.get("metadata") or {}).get("unbundle_role") not in (None, "turn1"))
+    print(f"input rows: {len(rows)}   output rows: {len(out)}")
+    print(f"split: {len(split_eids)}   greeting-only: {len(split_eids)-n_auth}   "
+          f"auth-in-history: {n_auth}")
+    print(f"tail rows: {n_tail}   unchanged: {len(rows)-len(split_eids)}")
+    print("INVARIANT OK: calls byte-identical to v3 for all "
+          f"{len(v3)} rows (trie unchanged).")
+    print(f"wrote {OUT.relative_to(ROOT)}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/unbundle/build_all_v5.py b/tempscripts/story_remediation/unbundle/build_all_v5.py
new file mode 100644
index 0000000000000000000000000000000000000000..1201f9509fd5120355f51d8ac7e36a1f7641f13e
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/build_all_v5.py
@@ -0,0 +1,323 @@
+"""V5 build: two prose-only cleanups on top of v4, calls still byte-identical to v3.
+
+  b1  method-aware auth handshake. v4 always asked "name and ZIP"; 83 greeting-only
+      rows actually authenticate by EMAIL (find_user_id_by_email), so the agent's
+      question now matches the auth tool the row already uses (email -> ask for the
+      email on file; name_zip -> ask for name + ZIP). No call changes.
+
+  b3  scrub raw argument id-tokens that leaked into dialogue (credit_card_..., 
+      gift_card_...). The customer/agent now say "my gift card" / "my card on file"
+      instead of pasting the internal id. The id still lives in the tool ARGUMENTS
+      (unchanged), so the executor / state db is unaffected.
+
+INVARIANT (asserted): every row's calls == v3's calls, byte for byte. Trie unchanged.
+Reads out/authored_v4.json (+v2 fallback, q1fix), writes out/trajectories_all_v5.jsonl.
+Run: python -u temp/story_remediation/unbundle/build_all_v5.py
+"""
+from __future__ import annotations
+import json, copy, hashlib, re
+from pathlib import Path
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+N100 = ROOT / "distractor_generation_2" / "datasets" / "n100" / "trajectories.jsonl"
+AUTHORED4 = HERE / "out" / "authored_v4.json"
+AUTHORED2 = HERE / "out" / "authored_v2.json"
+Q1FIX = HERE / "out" / "authored_q1fix_v3.json"
+V3 = HERE / "out" / "trajectories_all_v3.jsonl"
+OUT = HERE / "out" / "trajectories_all_v5.jsonl"
+
+AUTH_LEAD = ("find_user_id_by_name_zip", "get_user_details")
+FIND_METHOD = {"find_user_id_by_name_zip": "name_zip", "find_user_id_by_email": "email",
+               "find_user_id_by_phone": "phone", "find_user_id_by_username": "username"}
+
+OPENERS_VAGUE = [
+    "Hi, I need a hand with something on my account.",
+    "Hello, I'm hoping you can help me with one of my orders.",
+    "Hey there, I've got a question about my account.",
+    "Hi, could you help me sort something out on my account?",
+    "Hello, I need to take care of a couple of things on my order.",
+    "Hi, I was hoping to get some help with my account today.",
+    "Hey, I need help with something. Not sure who to ask.",
+    "Hi there, can you help me with an order issue?",
+]
+# b1: verify-ask pools keyed by the auth method the row actually uses
+VERIFY_ASK = {
+    "name_zip": [
+        "Of course, I'd be glad to help. First, can I verify your identity? Could you give me your full name and ZIP code?",
+        "Happy to help with that. Before I pull anything up, could you confirm your name and ZIP code for me?",
+        "Sure thing. To access your account I'll need to verify you first. What's your full name and ZIP code?",
+        "I can help with that. For security, could you share your full name and the ZIP code on your account?",
+        "Absolutely. Let me just verify you first. Can I get your name and ZIP code, please?",
+        "Glad to help. To start, could you confirm your full name and ZIP code so I can find your account?",
+    ],
+    "email": [
+        "Of course, I'd be glad to help. First, can I verify your identity? What's the email address on your account?",
+        "Happy to help with that. Before I pull anything up, could you confirm the email address on your account?",
+        "Sure thing. To access your account I'll need to verify you first. What email address is on the account?",
+        "I can help with that. For security, could you share the email address associated with your account?",
+        "Absolutely. Let me just verify you first. What's the email on file for your account?",
+        "Glad to help. To start, could you confirm the email address on your account so I can look you up?",
+    ],
+    "phone": [
+        "Of course, I'd be glad to help. First, can I verify your identity? What's the phone number on your account?",
+        "Happy to help. Before I pull anything up, could you confirm the phone number on file for your account?",
+        "Sure thing. To verify you, could you share the phone number associated with your account?",
+    ],
+    "username": [
+        "Of course, I'd be glad to help. First, can I verify you? Could you give me your account username?",
+        "Happy to help. Before I pull anything up, could you confirm the username on your account?",
+        "Sure thing. To verify you, what's the username on your account?",
+    ],
+}
+ID_PROVIDE = [
+    "Yeah, sure. It's {first} {last}, and the ZIP is {zip}.",
+    "Oh, right. {first} {last}, ZIP {zip}.",
+    "Of course, it's {first} {last}. ZIP code's {zip}.",
+    "Sure thing. Name's {first} {last}, and my ZIP is {zip}.",
+    "Um, ok. {first} {last}, and the ZIP on the account is {zip}.",
+]
+VERIFIED = [
+    "Thanks {first}, you're all verified. What can I do for you?",
+    "Great, I've got your account pulled up, {first}. How can I help?",
+    "You're all set, {first}. What would you like to do?",
+    "Perfect, verified. Thanks {first}. What can I help with?",
+]
+
+# b3: deterministic scrub of leaked argument id-tokens from NL (never touches calls)
+_APPOS = re.compile(r",?\s*(?:the\s+)?id\s+is\s+(?:gift_card_\w+|credit_card_\w+)", re.I)
+_GC_AFTER = re.compile(r"(gift card)\s+gift_card_\w+", re.I)
+_CC_AFTER = re.compile(r"(credit card|card)\s+credit_card_\w+", re.I)
+_GC_BARE = re.compile(r"\bgift_card_\w+")
+_CC_BARE = re.compile(r"\bcredit_card_\w+")
+_SPACE = re.compile(r"\s{2,}")
+
+
+def scrub(text: str, role: str) -> str:
+    if not text or ("_card_" not in text):
+        return text
+    mine = "your" if role == "assistant" else "my"
+    t = _APPOS.sub("", text)
+    t = _GC_AFTER.sub(r"\1", t)
+    t = _CC_AFTER.sub(r"\1", t)
+    t = _GC_BARE.sub(f"{mine} gift card", t)
+    t = _CC_BARE.sub(f"{mine} card on file", t)
+    t = t.replace(" ,", ",").replace(" .", ".").replace(" ?", "?")
+    t = _SPACE.sub(" ", t).strip()
+    return t
+
+
+def hist_of(r):
+    return r.get("history") or (r.get("metadata") or {}).get("history") or []
+
+
+def umsg(c):
+    return {"role": "user", "content": c, "tool_calls": [], "tool_call_id": None}
+
+
+def amsg(content=None, tool_calls=None):
+    return {"role": "assistant", "content": content,
+            "tool_calls": copy.deepcopy(tool_calls) if tool_calls else [],
+            "tool_call_id": None}
+
+
+def tmsg(call):
+    return {"role": "tool", "content": call.get("output"), "tool_calls": [], "tool_call_id": None}
+
+
+def pick(lst, eid, salt=""):
+    return lst[int(hashlib.md5((salt + eid).encode()).hexdigest(), 16) % len(lst)]
+
+
+def greeting_of(r):
+    h = hist_of(r)
+    if h and h[0].get("role") == "assistant" and not h[0].get("tool_calls") and h[0].get("content"):
+        return copy.deepcopy(h[0])
+    return amsg(content="Hi! How can I help you today?")
+
+
+def leading_auth(r):
+    lead = []
+    for m in hist_of(r):
+        for t in (m.get("tool_calls") or []):
+            if t["name"] in AUTH_LEAD:
+                lead.append(copy.deepcopy(t))
+    kept = []
+    for t in lead:
+        if not kept and t["name"] == "find_user_id_by_name_zip":
+            kept.append(t)
+        elif kept and t["name"] == "get_user_details":
+            kept.append(t); break
+        else:
+            break
+    return kept
+
+
+def auth_method(r):
+    for c in r["calls"]:
+        if c["name"] in FIND_METHOD:
+            return FIND_METHOD[c["name"]]
+    return "name_zip"
+
+
+def base_history(r):
+    """(cleaned_history, had_auth). b1: verify-ask matches the row's auth method."""
+    eid = r["example_id"]
+    greet = greeting_of(r)
+    opener = umsg(pick(OPENERS_VAGUE, eid, "op"))
+    kept = leading_auth(r)
+    method = "name_zip" if kept else auth_method(r)   # auth-in-history rows are name_zip
+    ask = amsg(content=pick(VERIFY_ASK[method], eid, "ask"))
+    if not kept:
+        return [greet, opener, ask], False
+    a = kept[0].get("arguments", {})
+    first = a.get("first_name", ""); last = a.get("last_name", ""); zp = a.get("zip", "")
+    idp = umsg(pick(ID_PROVIDE, eid, "idp").format(first=first, last=last, zip=zp))
+    verified = amsg(content=pick(VERIFIED, eid, "ok").format(first=first or "there"))
+    hist = [greet, opener, ask, idp]
+    for t in kept:
+        hist += [amsg(tool_calls=[t]), tmsg(t)]
+    hist += [verified]
+    return hist, True
+
+
+def calls_sig(calls):
+    return [(c.get("name"), json.dumps(c.get("arguments", {}), sort_keys=True, ensure_ascii=False))
+            for c in (calls or [])]
+
+
+def main():
+    rows = [json.loads(l) for l in open(N100, encoding="utf-8") if l.strip()]
+    a4 = json.loads(AUTHORED4.read_text(encoding="utf-8"))
+    a2 = json.loads(AUTHORED2.read_text(encoding="utf-8"))
+    q1fix = json.loads(Q1FIX.read_text(encoding="utf-8")) if Q1FIX.exists() else {}
+    v3 = {json.loads(l)["example_id"]: json.loads(l)
+          for l in open(V3, encoding="utf-8") if l.strip()}
+    v3_split = {r["metadata"]["orig_eid"] for r in v3.values()
+                if (r.get("metadata") or {}).get("unbundle_role") == "turn1"}
+
+    def bundle(eid):
+        b = a4.get(eid)
+        if b and "q1" in b and not b.get("_err"):
+            return b
+        b = a2.get(eid)
+        if b and "q1" in b and not b.get("_err"):
+            return b
+        return None
+
+    ok = {e: bundle(e) for e in a4 if bundle(e)}
+    for e in a2:
+        if e not in ok and bundle(e):
+            ok[e] = bundle(e)
+    print(f"usable bundles: {len(ok)}")
+
+    n_scrub = 0
+    out = []; split_eids = set(); n_auth = 0; method_ct = {"name_zip": 0, "email": 0, "phone": 0, "username": 0}
+    for r in rows:
+        eid = r["example_id"]
+        if eid not in ok or eid not in v3_split:
+            out.append(r); continue
+        sp = copy.deepcopy(ok[eid]); md = r["metadata"]; ad = md["anchor_depth"]
+        calls = r["calls"]; prefixF = calls[:ad + 1]; tail = calls[ad + 1:]
+        if len(tail) != len(sp["turns"]):
+            out.append(r); continue
+        base_prehist, had_auth = base_history(r)
+        if had_auth and eid in q1fix:
+            sp["q1"] = q1fix[eid]["q1"]
+        method_ct["name_zip" if had_auth else auth_method(r)] += 1
+        n_auth += int(had_auth); split_eids.add(eid)
+
+        # b3 scrub on every authored NL string (user + assistant)
+        def sc(txt, role):
+            nonlocal n_scrub
+            new = scrub(txt, role)
+            if new != txt:
+                n_scrub += 1
+            return new
+        sp["q1"] = sc(sp["q1"], "user")
+        sp["ack1"] = sc(sp["ack1"], "assistant")
+        sp["turns"] = [{"user": sc(t["user"], "user"), "ack": sc(t["ack"], "assistant")}
+                       for t in sp["turns"]]
+
+        t1 = copy.deepcopy(r)
+        t1["query"] = sp["q1"]; t1["calls"] = copy.deepcopy(prefixF)
+        t1["history"] = copy.deepcopy(base_prehist)
+        t1["metadata"] = copy.deepcopy(md)
+        t1["metadata"]["history"] = copy.deepcopy(base_prehist)
+        t1["metadata"]["unbundle_role"] = "turn1"; t1["metadata"]["orig_eid"] = eid
+        out.append(t1)
+
+        base_hist = (copy.deepcopy(base_prehist)
+                     + [umsg(sp["q1"]), amsg(tool_calls=prefixF)]
+                     + [tmsg(c) for c in prefixF]
+                     + [amsg(content=sp["ack1"])])
+        for i, call in enumerate(tail):
+            hist = copy.deepcopy(base_hist)
+            for j in range(i):
+                cj = tail[j]
+                hist += [umsg(sp["turns"][j]["user"]), amsg(tool_calls=[cj]),
+                         tmsg(cj), amsg(content=sp["turns"][j]["ack"])]
+            trow = copy.deepcopy(r)
+            trow["example_id"] = f"{eid}-t{i + 2}"
+            trow["query"] = sp["turns"][i]["user"]
+            trow["calls"] = [copy.deepcopy(call)]
+            trow["history"] = hist
+            trow["metadata"] = copy.deepcopy(md)
+            trow["metadata"]["history"] = copy.deepcopy(hist)
+            trow["metadata"]["unbundle_role"] = f"turn{i + 2}"
+            trow["metadata"]["orig_eid"] = eid
+            out.append(trow)
+
+    # b3 final pass: scrub any remaining card tokens in dialogue NL across ALL rows
+    # (covers passthrough/original confuser queries + histories). Tool outputs (role
+    # == "tool") and call arguments are left untouched, so calls/state db are intact.
+    for r in out:
+        if r.get("query") and "_card_" in r["query"]:
+            new = scrub(r["query"], "user")
+            if new != r["query"]:
+                r["query"] = new; n_scrub += 1
+        for m in (r.get("history") or []):
+            role = m.get("role")
+            if role in ("user", "assistant") and m.get("content") and "_card_" in m["content"]:
+                new = scrub(m["content"], role)
+                if new != m["content"]:
+                    m["content"] = new; n_scrub += 1
+        md = r.get("metadata") or {}
+        for m in (md.get("history") or []):
+            role = m.get("role")
+            if role in ("user", "assistant") and m.get("content") and "_card_" in m["content"]:
+                new = scrub(m["content"], role)
+                if new != m["content"]:
+                    m["content"] = new; n_scrub += 1
+
+    v5 = {r["example_id"]: r for r in out}
+    assert set(v5) == set(v3), "row-id set changed vs v3"
+    bad = [eid for eid in v3 if calls_sig(v3[eid]["calls"]) != calls_sig(v5[eid]["calls"])]
+    assert not bad, f"CALLS CHANGED vs v3 for {len(bad)} rows, e.g. {bad[:5]}"
+
+    # b3 sanity: no leaked card tokens remain anywhere in NL
+    leftover = []
+    for r in out:
+        txts = [r.get("query") or ""]
+        for src in (r.get("history") or []), ((r.get("metadata") or {}).get("history") or []):
+            txts += [m.get("content") or "" for m in src if m.get("role") != "tool"]
+        for t in txts:
+            if re.search(r"gift_card_\w+|credit_card_\w+", t):
+                leftover.append(r["example_id"]); break
+    assert not leftover, f"card tokens still in NL for {len(leftover)} rows: {leftover[:5]}"
+
+    OUT.parent.mkdir(parents=True, exist_ok=True)
+    with OUT.open("w", encoding="utf-8") as fh:
+        for r in out:
+            fh.write(json.dumps(r, ensure_ascii=False) + "\n")
+
+    print(f"input rows: {len(rows)}   output rows: {len(out)}")
+    print(f"split: {len(split_eids)}   greeting-only: {len(split_eids)-n_auth}   auth-in-history: {n_auth}")
+    print(f"b1 verify-ask by method: {method_ct}")
+    print(f"b3 NL strings scrubbed: {n_scrub}   (leftover card tokens: {len(leftover)})")
+    print(f"INVARIANT OK: calls byte-identical to v3 for all {len(v3)} rows (trie unchanged).")
+    print(f"wrote {OUT.relative_to(ROOT)}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/unbundle/build_all_v6.py b/tempscripts/story_remediation/unbundle/build_all_v6.py
new file mode 100644
index 0000000000000000000000000000000000000000..9992627918af505a212d3bfe3587b981e08ba656
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/build_all_v6.py
@@ -0,0 +1,187 @@
+"""Build v6 from v5: prose-only deterministic auth/identity fixes (calls-invariant).
+
+Fixes (all in authored NL only, never in `calls`):
+  1. name_mismatch      -- agent addresses customer by a name != auth first_name
+  2. dup_verification   -- >1 "you're verified" confirmation; keep the first, strip rest
+  3. zip_mismatch       -- customer states a ZIP (in a zip context) != auth zip
+  4. userid_in_prose    -- user speaks their internal user_id token (e.g. xan_rho_6699)
+
+Rendering defects the C3 judge cited (raw-JSON assistant content, markdown/bold in
+user messages) do NOT exist in the data -- 0 occurrences -- so nothing to fix there;
+the judge hallucinated them. (Verified by rendering the cited row.)
+
+Reads : temp/story_remediation/unbundle/out/trajectories_all_v5.jsonl
+Writes: temp/story_remediation/unbundle/out/trajectories_all_v6.jsonl
+"""
+import json, re, sys, copy
+sys.path.insert(0, r"temp/story_remediation/unbundle")
+import auth_lint_v5 as L
+
+SRC = r"temp/story_remediation/unbundle/out/trajectories_all_v5.jsonl"
+OUT = r"temp/story_remediation/unbundle/out/trajectories_all_v6.jsonl"
+
+ZIP_SUB_RX = None  # built per-row
+
+
+def strip_verif(text):
+    """Remove a verification-confirmation clause, keep the rest of the sentence."""
+    t = text
+    t = re.sub(r",?\s*you'?re (all )?verified", "", t, flags=re.I)
+    t = re.sub(r",?\s*you are (all )?verified", "", t, flags=re.I)
+    t = re.sub(r"Perfect,\s*verified\.\s*", "", t, flags=re.I)
+    t = re.sub(r"(Yep,?\s*|Yes,?\s*)?I'?ve verified your identity(?: (?:using|with) code \d+)?\.\s*", "", t, flags=re.I)
+    t = re.sub(r"I'?ve verified your account and\s*", "I've ", t, flags=re.I)
+    t = re.sub(r"\s{2,}", " ", t)
+    t = re.sub(r"^[,.\s]+", "", t)
+    t = t.replace(" .", ".").replace(" ,", ",").strip()
+    if t and t[0].islower():
+        t = t[0].upper() + t[1:]
+    return t
+
+
+def fix_row(r):
+    changed = []
+    method, first, last, zipc, email = L.auth_identity(r)
+
+    # --- collect wrong names (agent-spoken first names != auth first name) ---
+    allowed = {x.lower() for x in (first, last) if x}
+    wrong_names = set()
+    for role, c in L.convo_turns(r):
+        if role != "assistant":
+            continue
+        for m in list(L.ADDR_RX.finditer(c)) + list(L.ADDR_RX2.finditer(c)):
+            tok = m.group(1)
+            if tok in L.STOP:
+                continue
+            if allowed and tok.lower() not in allowed:
+                wrong_names.add(tok)
+
+    # --- mismatched zips (spoken in a zip-context, != auth zip, not a call-arg value) ---
+    argvals = L.call_arg_values(r)
+    bad_zips = set()
+    if zipc:
+        for role, c in L.convo_turns(r):
+            for m in L.ZIP_CTX_RX.finditer(c):
+                z = m.group(1)
+                if z != str(zipc) and z.lower() not in argvals:
+                    bad_zips.add(z)
+
+    # --- user_id token spoken by the user ---
+    uid_rx = None
+    if first and last:
+        uid_rx = re.compile(r"\b" + re.escape(first.lower()) + r"_" + re.escape(last.lower()) + r"_\d+\b")
+
+    # user self-identification with a wrong first name (last name matches, framed as a
+    # self-intro -- NOT "my spouse's account ... <OtherName>")
+    selfid_rx = None
+    if first and last:
+        selfid_rx = re.compile(
+            r"(it'?s|it is|i'?m|i am|this is|name'?s|name is)\s+([A-Z][a-z]+)\s+" + re.escape(last) + r"\b")
+
+    def fix_content(role, content):
+        nonlocal changed
+        if not content:
+            return content, False
+        new = content
+        # (1) name mismatch -- assistant only
+        if role == "assistant":
+            for wn in wrong_names:
+                if first:
+                    n2 = re.sub(r"\b" + re.escape(wn) + r"\b", first, new)
+                    if n2 != new:
+                        new = n2; changed.append("name_mismatch")
+        # (3) zip mismatch -- replace inside the zip context, any role
+        for bz in bad_zips:
+            n2 = re.sub(r"(zip\D{0,12})" + re.escape(bz), r"\g<1>" + str(zipc), new, flags=re.I)
+            if n2 != new:
+                new = n2; changed.append("zip_mismatch")
+        # (4) user_id token -- user only
+        if role == "user" and uid_rx is not None:
+            repl = (first + " " + last)
+            n2 = uid_rx.sub(repl, new)
+            if n2 != new:
+                new = n2; changed.append("userid_in_prose")
+        # (5) user self-intro wrong first name -- user only
+        if role == "user" and selfid_rx is not None:
+            def _sid(m):
+                if m.group(2).lower() == first.lower():
+                    return m.group(0)
+                return f"{m.group(1)} {first} {last}"
+            n2 = selfid_rx.sub(_sid, new)
+            if n2 != new:
+                new = n2; changed.append("selfid_name_mismatch")
+        return new, (new != content)
+
+    # apply name/zip/uid fixes across history + query
+    for h in r.get("history", []):
+        if h.get("role") in ("user", "assistant") and h.get("content"):
+            nc, _ = fix_content(h["role"], h["content"])
+            h["content"] = nc
+    if r.get("query"):
+        r["query"], _ = fix_content("user", r["query"])
+    # mirror into embedded metadata.history for self-consistency
+    for h in (r.get("metadata", {}).get("history") or []):
+        if h.get("role") in ("user", "assistant") and h.get("content"):
+            nc, _ = fix_content(h["role"], h["content"])
+            h["content"] = nc
+
+    # (2) dup verification -- keep FIRST confirmation, strip subsequent ones.
+    # Walk the conversation in render order (history then query), stripping in-place.
+    seen_verif = False
+
+    def walk_strip(entries):
+        nonlocal seen_verif
+        for h in entries:
+            if h.get("role") == "assistant" and h.get("content") and L.VERIFIED_RX.search(h["content"]):
+                if seen_verif:
+                    stripped = strip_verif(h["content"])
+                    if stripped != h["content"]:
+                        h["content"] = stripped
+                        changed.append("dup_verification")
+                else:
+                    seen_verif = True
+
+    walk_strip(r.get("history", []))
+    # query is user role -> never a verification confirmation; skip
+    # mirror strip in metadata.history using an independent pass
+    seen2 = False
+    for h in (r.get("metadata", {}).get("history") or []):
+        if h.get("role") == "assistant" and h.get("content") and L.VERIFIED_RX.search(h["content"]):
+            if seen2:
+                h["content"] = strip_verif(h["content"])
+            else:
+                seen2 = True
+
+    return changed
+
+
+def main():
+    rows = [json.loads(l) for l in open(SRC, encoding="utf-8")]
+    src_calls = [json.dumps(r["calls"], sort_keys=True) for r in rows]
+    from collections import Counter
+    tally = Counter()
+    touched = 0
+    for r in rows:
+        ch = fix_row(r)
+        if ch:
+            touched += 1
+            for k in set(ch):
+                tally[k] += 1
+    # calls invariant assert
+    new_calls = [json.dumps(r["calls"], sort_keys=True) for r in rows]
+    assert src_calls == new_calls, "CALLS CHANGED -- aborting"
+
+    with open(OUT, "w", encoding="utf-8") as f:
+        for r in rows:
+            f.write(json.dumps(r) + "\n")
+
+    print("v6 built:", OUT)
+    print("rows touched:", touched)
+    print("fix tally (rows with each fix type):")
+    for k in ["name_mismatch", "dup_verification", "zip_mismatch", "userid_in_prose", "selfid_name_mismatch"]:
+        print(f"  {k:16s} {tally[k]}")
+    print("calls invariant vs v5: OK (byte-identical)")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/unbundle/build_v3.py b/tempscripts/story_remediation/unbundle/build_v3.py
new file mode 100644
index 0000000000000000000000000000000000000000..f5e24c03889f252300cba91a21ee9ffc11af80cc
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/build_v3.py
@@ -0,0 +1,141 @@
+"""Unbundle prototype: split a confuser's single harvested mega-turn into TWO
+turns at the trie divergence point (metadata.anchor_depth).
+
+For each candidate:
+  turn1 (T1, the PRIMARY confuser, retrieval target preserved):
+     query = narrowed q1 (only warrants prefix + F, the infiltration node)
+     calls = orig_calls[:anchor_depth+1]      (prefix + F)   <- still diverges
+             at anchor_depth with F, exactly as before
+     history = original history (unchanged)
+  turn2 (T2, the cut tail, re-rooted as its own trie path):
+     query = q2 (a fresh user request motivating the tail)
+     calls = orig_calls[anchor_depth+1:]       (G..Z)
+     history = original history + [q1, assistant(tool_calls=prefix+F, real
+               recorded outputs reused verbatim), bridge]  -> auth already done,
+               T2 does NOT re-auth (matches tau2: authenticate once, early)
+
+C3 blinds tool names, so the confuser/fictional tools in the tail are fine; we
+only repartition the row's OWN existing calls across two turns (no new tools,
+no fabricated outputs).
+
+Writes out/trajectories_v3.jsonl (20 rows: 10 T1 + 10 T2).
+Run: python -u temp/story_remediation/unbundle/build_v3.py
+"""
+from __future__ import annotations
+import json, copy
+from pathlib import Path
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+N100 = ROOT / "distractor_generation_2" / "datasets" / "n100" / "trajectories.jsonl"
+OUT = HERE / "out" / "trajectories_v3.jsonl"
+
+# Authored splits: q1 (narrowed turn-1), bridge (assistant reply after turn1),
+# q2 (turn-2 user request for the tail). Entities reuse ids already in the query.
+SPLITS = {
+ "confuser-add_gift_message-227": dict(
+   q1="On my pending gift order #W3410100, please add the gift message 'Happy Graduation!'.",
+   bridge="Done, I've added the gift message 'Happy Graduation!' to order #W3410100.",
+   q2="Thanks. Separately, for my delivered order #W3410200, can you give me a printable return label?"),
+ "confuser-get_return_label-271": dict(
+   q1="Now to my orders - I need a printable prepaid return label for #W5590123.",
+   bridge="Here's your prepaid return label for #W5590123, emailed as a printable PDF.",
+   q2="Great. One more - for #W2201984, can you send a gift receipt with no prices?"),
+ "confuser-request_gift_receipt-195": dict(
+   q1="For my order #W3320800, which was a gift, I need a gift receipt with no prices.",
+   bridge="Done - here's the no-price gift receipt for #W3320800.",
+   q2="Thanks. Could you also pull a copy of the tax invoice for my records, and a printable return label in case the recipient wants to send it back?"),
+ "confuser-get_shipping_options-215": dict(
+   q1="For my pending order #W5567012, what shipping options and speeds are available?",
+   bridge="Here are the available shipping options and speeds for #W5567012.",
+   q2="Got it. I'd also like to book a professional installation for the treadmill, and can you split the order into two shipments so the weights come separately?"),
+ "confuser-redeem_loyalty_points-163": dict(
+   q1="I've got a lot of loyalty points - can you redeem 2,000 of them for store credit?",
+   bridge="Done - I've redeemed 2,000 loyalty points for store credit.",
+   q2="Great. Can you tell me my resulting store-credit balance, the balance on gift card gift_card_9981220, and what promotions are running right now?"),
+ "confuser-get_size_guide-199": dict(
+   q1="On the trail shoes, can you pull up the sizing chart?",
+   bridge="Here's the sizing chart for the trail shoes.",
+   q2="Thanks. A few more things: sign me up for a restock alert on the black pair (item 1152271459) since it's sold out, register the warranty on the pair I already bought (item 4402019500), and post a 5-star review saying 'Great grip on wet trails.'"),
+ "confuser-get_gift_card_balance-346": dict(
+   q1="Before I finalize order #W3401200, can you tell me the balance on my gift card gift_card_3401120?",
+   bridge="Here's the current balance on gift card gift_card_3401120.",
+   q2="Thanks. And what promotions are currently running?"),
+ "confuser-get_warranty_details-281": dict(
+   q1="I just received my air purifier from order #W6042219 and I'd like to know the manufacturer's warranty terms on it - how long it's covered and what it includes.",
+   bridge="Here are the manufacturer's warranty terms for your air purifier from order #W6042219.",
+   q2="Perfect. Can you go ahead and register that warranty under my account so it's active?"),
+ "confuser-get_warranty_details-455": dict(
+   q1="For the jacket (item 3566100900) in my order #W3566100, can you show the warranty coverage? My email is cara.vin@example.com.",
+   bridge="Here's the warranty coverage for the jacket (item 3566100900).",
+   q2="Thanks. Could you also show the extended-warranty plans and the sizing chart for it?"),
+ "confuser-file_shipping_insurance_claim-296": dict(
+   q1="My order #W5540921 was a gift that arrived damaged - please file a shipping-insurance claim.",
+   bridge="I've filed a shipping-insurance claim for order #W5540921.",
+   q2="Thank you. Can you also send me a printable return label, and a gift receipt with no prices so the recipient can exchange it?"),
+}
+
+
+def hist_of(r):
+    return r.get("history") or (r.get("metadata") or {}).get("history") or []
+
+
+def main():
+    rows = {json.loads(l)["example_id"]: json.loads(l)
+            for l in open(N100, encoding="utf-8") if l.strip()}
+    out = []
+    for eid, sp in SPLITS.items():
+        r = rows[eid]
+        md = r["metadata"]; ad = md["anchor_depth"]
+        calls = r["calls"]
+        t1_calls = calls[:ad + 1]
+        tail_calls = calls[ad + 1:]
+        assert tail_calls, f"{eid}: empty tail"
+        orig_hist = hist_of(r)
+
+        # ---- T1: primary confuser, tail removed, query narrowed ----
+        t1 = copy.deepcopy(r)
+        t1["query"] = sp["q1"]
+        t1["calls"] = copy.deepcopy(t1_calls)
+        t1["history"] = copy.deepcopy(orig_hist)
+        t1["metadata"] = copy.deepcopy(md)
+        t1["metadata"]["history"] = copy.deepcopy(orig_hist)
+        t1["metadata"]["unbundle_role"] = "turn1"
+        t1["metadata"]["orig_eid"] = eid
+        out.append(t1)
+
+        # ---- T2: the cut tail, re-rooted; turn1 shown as completed history ----
+        t1_assistant = {"role": "assistant", "content": None,
+                        "tool_calls": copy.deepcopy(t1_calls), "tool_call_id": None}
+        tool_msgs = [{"role": "tool", "content": c.get("output"),
+                      "tool_calls": [], "tool_call_id": None} for c in t1_calls]
+        bridge_hist = (copy.deepcopy(orig_hist)
+                       + [{"role": "user", "content": sp["q1"], "tool_calls": [], "tool_call_id": None},
+                          t1_assistant]
+                       + tool_msgs
+                       + [{"role": "assistant", "content": sp["bridge"], "tool_calls": [], "tool_call_id": None}])
+        t2 = copy.deepcopy(r)
+        t2["example_id"] = eid + "-t2"
+        t2["query"] = sp["q2"]
+        t2["calls"] = copy.deepcopy(tail_calls)
+        t2["history"] = bridge_hist
+        t2["metadata"] = copy.deepcopy(md)
+        t2["metadata"]["history"] = copy.deepcopy(bridge_hist)
+        t2["metadata"]["unbundle_role"] = "turn2"
+        t2["metadata"]["orig_eid"] = eid
+        out.append(t2)
+
+    OUT.parent.mkdir(parents=True, exist_ok=True)
+    with OUT.open("w", encoding="utf-8") as fh:
+        for r in out:
+            fh.write(json.dumps(r, ensure_ascii=False) + "\n")
+
+    print(f"wrote {len(out)} rows ({len(SPLITS)} T1 + {len(SPLITS)} T2) -> {OUT.relative_to(ROOT)}")
+    for eid, sp in SPLITS.items():
+        r = rows[eid]; ad = r["metadata"]["anchor_depth"]
+        cn = [c["name"] for c in r["calls"]]
+        print(f"  {eid}: T1 calls={cn[:ad+1]}  |  T2 calls={cn[ad+1:]}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/unbundle/diagnose_caught_v5.py b/tempscripts/story_remediation/unbundle/diagnose_caught_v5.py
new file mode 100644
index 0000000000000000000000000000000000000000..b3e7633c33b03876ca74f3a9ff1d09bb17f35647
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/diagnose_caught_v5.py
@@ -0,0 +1,181 @@
+"""Why did C3 catch the v5 synthetics? Re-judge every CAUGHT v5 row once, capture
+the judge's own `reasoning`, and bucket the tells into interpretable categories.
+
+The main run (C3_all_v5.jsonl) stored only guesses, so we re-run the identical C3
+prompt on the 543 caught rows, keep the reasoning, and classify each into one
+primary bucket (priority order below) plus multi-label overlap counts.
+
+Saves out/caught_reasons_v5.jsonl (eid, role, sample_caught, guess, reasoning,
+buckets) and prints the breakdown.
+Run: python -u temp/story_remediation/unbundle/diagnose_caught_v5.py
+"""
+from __future__ import annotations
+import json, logging, sys, collections
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+import yaml
+
+for _n in ("azure", "azure.identity", "azure.core.pipeline.policies.http_logging_policy"):
+    logging.getLogger(_n).setLevel(logging.WARNING)
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+sys.path.insert(0, str(ROOT))
+from datasetreview import pipelines as P            # noqa: E402
+from datasetreview import judge_prompts as J        # noqa: E402
+from datasetreview.llm_client import make_judge      # noqa: E402
+
+OUT = HERE / "out"
+cfg = yaml.safe_load(open(ROOT / "datasetreview" / "config.yaml", encoding="utf-8"))
+BASELINE = ROOT / "datasetreview" / "results" / "new" / "C3.jsonl"
+WORKERS = max(8, cfg["run"].get("workers", 4))
+
+verds = [json.loads(l) for l in open(OUT / "C3_all_v5.jsonl", encoding="utf-8") if l.strip()]
+fakes = {e["example_id"]: e for e in
+         (json.loads(l) for l in open(OUT / "trajectories_all_v5.jsonl", encoding="utf-8") if l.strip())}
+base = {}
+for line in open(BASELINE, encoding="utf-8"):
+    if line.strip():
+        d = json.loads(line); base[d["item_id"]] = d
+
+reals = P.real_trajectories()
+pairer = P.make_pairer(reals)
+judge = make_judge(cfg["model"])
+
+caught = [v for v in verds if v.get("caught")]
+
+# bucket -> keyword list. A reasoning may hit several; primary = first in PRIORITY.
+BUCKETS = {
+    "A_capability_scenario_realism": [
+        "capab", "unrealistic", "not realistic", "unusual request", "unusual", "atypical",
+        "wouldn't", "would not", "implausible", "unlikely", "niche", "oddly specific",
+        "fabricat", "made-up", "made up", "obscure", "specialized", "nonstandard",
+        "non-standard", "not a standard", "not standard", "real system", "real assistant",
+        "real agent", "real company", "real retailer", "actual system", "plausib",
+        "unusual feature", "feature", "functionalit", "such a tool", "these tools"],
+    "B_multitask_bundling": [
+        "unrelated", "multiple different", "several different", "range of", "variety",
+        "jumps between", "disparate", "disjoint", "laundry list", "checklist",
+        "many tasks", "multiple tasks", "multiple requests", "switches", "different topics",
+        "grab bag", "one after another", "rapid succession", "back-to-back", "so many",
+        "numerous", "series of", "list of requests", "everything at once"],
+    "D_auth_verification": [
+        "verif", "identity", "authent", "security", "no verification", "without verif",
+        "didn't verify", "skipped verif", "no auth"],
+    "C_frictionless_smooth": [
+        "friction", "too smooth", "seamless", "efficient", "effortless", "no pushback",
+        "no hesitat", "compliant", "too easy", "too well", "goes smoothly", "flawless",
+        "no complications", "no issues", "everything works", "cooperat", "accommodat"],
+    "E_agent_phrasing_templated": [
+        "formal", "generic", "templat", "robotic", "scripted", "canned", "stiff",
+        "overly polite", "professional", "polished", "assistant's phrasing",
+        "assistant phrasing", "agent's phrasing", "agent phrasing", "customer service",
+        "corporate", "helpful assistant"],
+    "F_customer_phrasing": [
+        "customer", "user's phrasing", "user phrasing", "casual", "disfluen", "filler",
+        "hedg", "overly casual", "forced", "trying too hard", "stilted", "awkward",
+        "too articulate", "too clear", "well-structured", "well structured", "organized",
+        "coherent", "natural", "colloquial", "conversational"],
+    "G_structure_brevity_history": [
+        "abrupt", "terse", "brief", "short", "curt", "clipped", "history", "prior",
+        "previous", "context", "follow-up", "follow up", "continuation", "disconnect",
+        "out of nowhere", "no context", "sudden", "transition"],
+}
+PRIORITY = ["A_capability_scenario_realism", "B_multitask_bundling", "D_auth_verification",
+            "C_frictionless_smooth", "E_agent_phrasing_templated", "F_customer_phrasing",
+            "G_structure_brevity_history"]
+
+
+def label(reason: str):
+    low = reason.lower()
+    hits = [b for b in PRIORITY if any(k in low for k in BUCKETS[b])]
+    primary = hits[0] if hits else "H_other"
+    return primary, hits
+
+
+def judge_one(v):
+    eid = v["item_id"]; fake = fakes.get(eid)
+    if not fake:
+        return None
+    real = pairer(fake)
+    swap = (base.get(eid) or base.get(v.get("orig_eid")) or {}).get("answer_key") == "B"
+    msgs = J.build_c3(fake, real, swap=swap)
+    key = msgs["answer_key"]
+    try:
+        r = judge.judge({"system": msgs["system"], "user": msgs["user"]})
+    except Exception as e:  # noqa: BLE001
+        return {"item_id": eid, "role": v.get("role"), "error": str(e)}
+    reason = (r.get("reasoning") or "").strip()
+    primary, hits = label(reason)
+    return {"item_id": eid, "role": v.get("role"), "guess": r.get("guess"),
+            "sample_caught": r.get("guess") == key, "primary": primary,
+            "buckets": hits, "reasoning": reason}
+
+
+def main():
+    print(f"re-judging {len(caught)} caught rows (workers={WORKERS}) to capture reasoning...")
+    with ThreadPoolExecutor(max_workers=WORKERS) as ex:
+        rows = [x for x in ex.map(judge_one, caught) if x]
+    errs = [r for r in rows if r.get("error")]
+    good = [r for r in rows if not r.get("error")]
+    (OUT / "caught_reasons_v5.jsonl").write_text(
+        "\n".join(json.dumps(r) for r in rows) + "\n", encoding="utf-8")
+
+    recaught = [r for r in good if r["sample_caught"]]
+    # distribution over rows that also caught on this sample (true catch-reasons)
+    prim = collections.Counter(r["primary"] for r in recaught)
+    multi = collections.Counter()
+    for r in recaught:
+        for b in r["buckets"]:
+            multi[b] += 1
+    n = len(recaught)
+
+    NAMES = {
+        "A_capability_scenario_realism": "capability / scenario realism (tool or task seems unreal)",
+        "B_multitask_bundling": "multi-task bundling (many / unrelated requests)",
+        "D_auth_verification": "auth / verification anomalies",
+        "C_frictionless_smooth": "too smooth / frictionless / compliant",
+        "E_agent_phrasing_templated": "agent phrasing (formal / generic / templated)",
+        "F_customer_phrasing": "customer phrasing (too clean / forced-casual / 'too natural')",
+        "G_structure_brevity_history": "structure / brevity / history-flow",
+        "H_other": "other / unclassified",
+    }
+
+    print("\n" + "=" * 80)
+    print(f"CAUGHT-REASON BREAKDOWN  (v5, original C3 prompt)")
+    print(f"  caught rows re-judged: {len(good)}   errors: {len(errs)}")
+    print(f"  of those, this sample also caught: {n}  (reasoning below is over these)")
+    print("=" * 80)
+    print("\nPRIMARY tell (each row assigned one bucket, priority-ordered):")
+    for b, c in prim.most_common():
+        print(f"  {c:4d}  {c/n:5.1%}   {NAMES.get(b, b)}")
+    print("\nANY-MENTION (multi-label; a row can hit several tells):")
+    for b, c in multi.most_common():
+        print(f"  {c:4d}  {c/n:5.1%}   {NAMES.get(b, b)}")
+
+    # split primary distribution by role (T1 vs tail)
+    print("\nPRIMARY tell by row type:")
+    for grp, pred in (("turn1 (trie slot)", lambda r: r["role"] == "turn1"),
+                      ("tail", lambda r: (r["role"] or "").startswith("turn") and r["role"] != "turn1"),
+                      ("passthrough", lambda r: not r["role"])):
+        sub = [r for r in recaught if pred(r)]
+        if not sub:
+            continue
+        pc = collections.Counter(r["primary"] for r in sub)
+        top = ", ".join(f"{NAMES.get(b, b).split(' (')[0]} {c}" for b, c in pc.most_common(4))
+        print(f"  {grp:22s} n={len(sub):4d}   {top}")
+
+    print("\nExample reasonings per primary bucket (first 2):")
+    seen = collections.Counter()
+    for b in PRIORITY + ["H_other"]:
+        exs = [r for r in recaught if r["primary"] == b][:2]
+        if not exs:
+            continue
+        print(f"\n[{NAMES.get(b, b)}]")
+        for r in exs:
+            print(f"  ({r['item_id']}) {r['reasoning'][:280]}")
+    print(f"\nsaved -> {(OUT/'caught_reasons_v5.jsonl').relative_to(ROOT)}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/unbundle/diagnose_tail.py b/tempscripts/story_remediation/unbundle/diagnose_tail.py
new file mode 100644
index 0000000000000000000000000000000000000000..64b93dc915dc44f0538bf7c4cdaacabae796c757
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/diagnose_tail.py
@@ -0,0 +1,79 @@
+"""Diagnose WHY v3 tail turns still get caught: pull the judge's own reasoning.
+
+Samples still-caught tail rows (role turn2+), re-runs C3 once each with reasoning
+captured, prints the rationale, and tallies recurring tell-keywords so we can see
+the dominant factors rather than guessing.
+Run: python -u temp/story_remediation/unbundle/diagnose_tail.py [N]
+"""
+from __future__ import annotations
+import json, logging, sys, re, collections, random
+from pathlib import Path
+import yaml
+
+for _n in ("azure", "azure.identity", "azure.core.pipeline.policies.http_logging_policy"):
+    logging.getLogger(_n).setLevel(logging.WARNING)
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+sys.path.insert(0, str(ROOT))
+from datasetreview import pipelines as P            # noqa: E402
+from datasetreview import judge_prompts as J        # noqa: E402
+from datasetreview.llm_client import make_judge      # noqa: E402
+
+OUT = HERE / "out"
+cfg = yaml.safe_load(open(ROOT / "datasetreview" / "config.yaml", encoding="utf-8"))
+BASELINE = ROOT / "datasetreview" / "results" / "new" / "C3.jsonl"
+
+verds = [json.loads(l) for l in open(OUT / "C3_all_v3.jsonl", encoding="utf-8") if l.strip()]
+fakes = {e["example_id"]: e for e in
+         (json.loads(l) for l in open(OUT / "trajectories_all_v3.jsonl", encoding="utf-8") if l.strip())}
+base = {}
+for line in open(BASELINE, encoding="utf-8"):
+    if line.strip():
+        d = json.loads(line); base[d["item_id"]] = d
+
+reals = P.real_trajectories()
+pairer = P.make_pairer(reals)
+judge = make_judge(cfg["model"])
+
+caught_tails = [v for v in verds
+                if (v.get("role") or "").startswith("turn") and v.get("role") != "turn1"
+                and v.get("caught")]
+random.seed(7)
+random.shuffle(caught_tails)
+N = int(sys.argv[1]) if len(sys.argv) > 1 else 16
+sample = caught_tails[:N]
+
+KW = ["abrupt", "context", "history", "prior", "previous", "single", "one tool",
+      "efficient", "polished", "concise", "terse", "no clarif", "clarif", "confirm",
+      "generic", "templat", "formal", "assistant", "acknowled", "past tense",
+      "greeting", "identity", "auth", "repetit", "unnatural", "too clean", "smooth",
+      "brief", "short", "curt", "follow-up", "follow up", "disconnect", "abrupt",
+      "sequence", "unrelated", "jump", "no friction", "compliant"]
+tally = collections.Counter()
+
+print(f"caught tails total={len(caught_tails)}   sampling {len(sample)}\n" + "=" * 78)
+for v in sample:
+    eid = v["item_id"]; fake = fakes.get(eid)
+    if not fake:
+        continue
+    real = pairer(fake)
+    swap = (base.get(eid) or base.get(v.get("orig_eid")) or {}).get("answer_key") == "B"
+    msgs = J.build_c3(fake, real, swap=swap)
+    try:
+        r = judge.judge({"system": msgs["system"], "user": msgs["user"]})
+    except Exception as e:  # noqa: BLE001
+        print(f"[{eid}] ERROR {e}"); continue
+    reason = (r.get("reasoning") or "").strip()
+    low = reason.lower()
+    for k in KW:
+        if k in low:
+            tally[k] += 1
+    nturns = len(fake.get("history", [])) + 1
+    print(f"\n[{eid}]  role={v['role']}  guess={r.get('guess')}  turns_in_conv={nturns}")
+    print(f"  {reason}")
+
+print("\n" + "=" * 78 + "\nTELL KEYWORD TALLY (across sampled reasonings):")
+for k, c in tally.most_common():
+    if c:
+        print(f"  {c:3d}  {k}")
diff --git a/tempscripts/story_remediation/unbundle/diagnose_tail_v4.py b/tempscripts/story_remediation/unbundle/diagnose_tail_v4.py
new file mode 100644
index 0000000000000000000000000000000000000000..0d19eb2530b7fa0bf0bf7fed0978acfb1ff03e24
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/diagnose_tail_v4.py
@@ -0,0 +1,80 @@
+"""Diagnose WHY v3 tail turns still get caught: pull the judge's own reasoning.
+
+Samples still-caught tail rows (role turn2+), re-runs C3 once each with reasoning
+captured, prints the rationale, and tallies recurring tell-keywords so we can see
+the dominant factors rather than guessing.
+Run: python -u temp/story_remediation/unbundle/diagnose_tail.py [N]
+"""
+from __future__ import annotations
+import json, logging, sys, re, collections, random
+from pathlib import Path
+import yaml
+
+for _n in ("azure", "azure.identity", "azure.core.pipeline.policies.http_logging_policy"):
+    logging.getLogger(_n).setLevel(logging.WARNING)
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+sys.path.insert(0, str(ROOT))
+from datasetreview import pipelines as P            # noqa: E402
+from datasetreview import judge_prompts as J        # noqa: E402
+from datasetreview.llm_client import make_judge      # noqa: E402
+
+OUT = HERE / "out"
+cfg = yaml.safe_load(open(ROOT / "datasetreview" / "config.yaml", encoding="utf-8"))
+BASELINE = ROOT / "datasetreview" / "results" / "new" / "C3.jsonl"
+
+verds = [json.loads(l) for l in open(OUT / "C3_all_v4.jsonl", encoding="utf-8") if l.strip()]
+fakes = {e["example_id"]: e for e in
+         (json.loads(l) for l in open(OUT / "trajectories_all_v4.jsonl", encoding="utf-8") if l.strip())}
+base = {}
+for line in open(BASELINE, encoding="utf-8"):
+    if line.strip():
+        d = json.loads(line); base[d["item_id"]] = d
+
+reals = P.real_trajectories()
+pairer = P.make_pairer(reals)
+judge = make_judge(cfg["model"])
+
+caught_tails = [v for v in verds
+                if (v.get("role") or "").startswith("turn") and v.get("role") != "turn1"
+                and v.get("caught")]
+random.seed(7)
+random.shuffle(caught_tails)
+N = int(sys.argv[1]) if len(sys.argv) > 1 else 16
+sample = caught_tails[:N]
+
+KW = ["abrupt", "context", "history", "prior", "previous", "single", "one tool",
+      "efficient", "polished", "concise", "terse", "no clarif", "clarif", "confirm",
+      "generic", "templat", "formal", "assistant", "acknowled", "past tense",
+      "greeting", "identity", "auth", "repetit", "unnatural", "too clean", "smooth",
+      "brief", "short", "curt", "follow-up", "follow up", "disconnect", "abrupt",
+      "sequence", "unrelated", "jump", "no friction", "compliant"]
+tally = collections.Counter()
+
+print(f"caught tails total={len(caught_tails)}   sampling {len(sample)}\n" + "=" * 78)
+for v in sample:
+    eid = v["item_id"]; fake = fakes.get(eid)
+    if not fake:
+        continue
+    real = pairer(fake)
+    swap = (base.get(eid) or base.get(v.get("orig_eid")) or {}).get("answer_key") == "B"
+    msgs = J.build_c3(fake, real, swap=swap)
+    try:
+        r = judge.judge({"system": msgs["system"], "user": msgs["user"]})
+    except Exception as e:  # noqa: BLE001
+        print(f"[{eid}] ERROR {e}"); continue
+    reason = (r.get("reasoning") or "").strip()
+    low = reason.lower()
+    for k in KW:
+        if k in low:
+            tally[k] += 1
+    nturns = len(fake.get("history", [])) + 1
+    print(f"\n[{eid}]  role={v['role']}  guess={r.get('guess')}  turns_in_conv={nturns}")
+    print(f"  {reason}")
+
+print("\n" + "=" * 78 + "\nTELL KEYWORD TALLY (across sampled reasonings):")
+for k, c in tally.most_common():
+    if c:
+        print(f"  {c:3d}  {k}")
+
diff --git a/tempscripts/story_remediation/unbundle/dump_c3_view.py b/tempscripts/story_remediation/unbundle/dump_c3_view.py
new file mode 100644
index 0000000000000000000000000000000000000000..49dfcc367ae6b701ecc4df79145b0f737aba28f3
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/dump_c3_view.py
@@ -0,0 +1,31 @@
+"""Dump the exact CONV_A / CONV_B text the C3 judge sees for a given tail eid."""
+from __future__ import annotations
+import json, sys, os
+from pathlib import Path
+import yaml
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+sys.path.insert(0, str(ROOT))
+from datasetreview import pipelines as P
+from datasetreview import judge_prompts as J
+
+eid = sys.argv[1] if len(sys.argv) > 1 else "confuser-get_order_invoice-782-t2"
+fakes = {e["example_id"]: e for e in
+         (json.loads(l) for l in open(HERE / "out" / (os.environ.get("V4FILE") or "trajectories_all_v3.jsonl"), encoding="utf-8") if l.strip())}
+base = {}
+for line in open(ROOT / "datasetreview" / "results" / "new" / "C3.jsonl", encoding="utf-8"):
+    if line.strip():
+        d = json.loads(line); base[d["item_id"]] = d
+fake = fakes[eid]
+reals = P.real_trajectories()
+pairer = P.make_pairer(reals)
+real = pairer(fake)
+orig = fake.get("metadata", {}).get("orig_eid")
+swap = (base.get(eid) or base.get(orig) or {}).get("answer_key") == "B"
+msgs = J.build_c3(fake, real, swap=swap)
+print(f"eid={eid}  swap={swap}  answer_key={msgs['answer_key']}")
+print(f"history turns in fake: {len(fake.get('history', []))}")
+print("#" * 80)
+# extract just the two convs from the user message
+u = msgs["user"]
+print(u[u.index("---Conversation A---"):])
diff --git a/tempscripts/story_remediation/unbundle/fix_error_records.py b/tempscripts/story_remediation/unbundle/fix_error_records.py
new file mode 100644
index 0000000000000000000000000000000000000000..424e0968233bbc6eef46d0911a740298dd76683f
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/fix_error_records.py
@@ -0,0 +1,64 @@
+"""Re-judge the handful of records that hit a transient JSON-parse error on one of
+their 3 samples, and rewrite ONLY those lines in place (canonical record builders,
+so schema is unchanged). Makes the final C1/C3 JSONL pristine (3/3 samples, error=null).
+"""
+from __future__ import annotations
+import json, sys
+from pathlib import Path
+import yaml
+
+ROOT = Path(__file__).resolve().parents[3]
+sys.path.insert(0, str(ROOT))
+from datasetreview import pipelines as P          # noqa: E402
+from datasetreview.llm_client import make_judge   # noqa: E402
+from scripts import run_dataeval as R             # noqa: E402
+
+OUT = ROOT / "temp" / "story_remediation" / "unbundle" / "final_c1c3"
+V6 = ROOT / "temp" / "story_remediation" / "unbundle" / "out" / "trajectories_all_v6.jsonl"
+_ROWS = {json.loads(l)["example_id"]: json.loads(l)
+         for l in open(V6, encoding="utf-8") if l.strip()}
+P.confuser_trajectories = lambda level: list(_ROWS.values())
+
+FIX = {"C1": ["confuser-upgrade_shipping_speed-796-t3", "confuser-reorder_previous_order-311-t3",
+              "confuser-get_gift_card_balance-433"],
+       "C3": ["confuser-get_order_invoice-486-t4"]}
+SAMPLES = 3
+
+
+def rejudge(exp, ctx, judge, item_id):
+    pipe = P.PIPELINES[exp](ctx)
+    w = P.Work(100, item_id, _ROWS[item_id])
+    key = f"n100:{item_id}"
+    if exp == "C3":
+        per = []
+        for ms in pipe.build_all(w):
+            res = [judge.judge(ms["msgs"]) for _ in range(SAMPLES)]
+            per.append((ms["orientation"], ms["answer_key"], res))
+        return key, R._record_c3(exp, key, w, per, [])
+    msgs = pipe.build(w)
+    res = [judge.judge(msgs) for _ in range(SAMPLES)]
+    return key, R._record(exp, key, w, res, [], "verdict")
+
+
+def main():
+    cfg = yaml.safe_load((ROOT / "datasetreview" / "config.yaml").read_text(encoding="utf-8"))
+    judge = make_judge(cfg["model"])
+    ctx = P.build_context(list(FIX))
+    for exp, ids in FIX.items():
+        path = OUT / f"{exp}.jsonl"
+        recs = [json.loads(l) for l in open(path, encoding="utf-8") if l.strip()]
+        by_item = {r["item_id"]: i for i, r in enumerate(recs)}
+        for item_id in ids:
+            _, newrec = rejudge(exp, ctx, judge, item_id)
+            recs[by_item[item_id]] = newrec
+            print(f"{exp} {item_id}: error={newrec.get('error')} "
+                  f"verdict={newrec.get('verdict')} "
+                  f"n_samples={newrec.get('n_samples') or newrec.get('samples_per_orientation')}")
+        with open(path, "w", encoding="utf-8") as fh:
+            for r in recs:
+                fh.write(json.dumps(r, ensure_ascii=False) + "\n")
+        print(f"  rewrote {path} ({len(recs)} lines)")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/unbundle/replay_v5.py b/tempscripts/story_remediation/unbundle/replay_v5.py
new file mode 100644
index 0000000000000000000000000000000000000000..8dfdbac020b12d03220bf8aa4c1c0408395794c7
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/replay_v5.py
@@ -0,0 +1,186 @@
+"""Free-running state runthrough on the V5 unbundled trajectories.
+
+v5 changed ONLY dialogue (b1 method-aware verify-ask, b3 token scrub). `calls`
+are byte-identical to v3 / the source n100. This harness proves that at the level
+that matters for free-running execution:
+
+  1. RECONSTRUCTION INVARIANT: for every original episode, concatenating its v5
+     rows' calls in turn order (turn1, t2, t3, ...) reproduces the source n100
+     call list byte-for-byte. This is the real "no floating / dropped variables"
+     check for the split dataset -- if a rewrite had dropped or mangled an id,
+     the reconstruction would diverge from source.
+
+  2. FREE-RUNNING REPLAY: seed ONE EpisodeState per reconstructed episode
+     (from_trajectory reads only `calls` + catalog, never dialogue), then replay
+     the full ordered call sequence against that single evolving state and check
+     each output reproduces the recorded one. Because we replay the *whole*
+     episode (not per-row), money ops see the accumulated balances they need.
+
+Any exception / mismatch / skip_nodata here would be a genuine execution gap; if
+it stems from a db seed missing (gift card, order balance, cart subtotal), add it
+to systemUpgrade/executor/catalog.json and re-run.
+
+Run from repo root: python -u temp/story_remediation/unbundle/replay_v5.py
+"""
+from __future__ import annotations
+import json, sys, re
+from collections import Counter, defaultdict
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[3]
+EXEC = ROOT / "systemUpgrade" / "executor"
+sys.path.insert(0, str(EXEC))
+from fake_state import EpisodeState        # noqa: E402
+from fake_tools import TOOLS               # noqa: E402
+
+catalog = json.load(open(EXEC / "catalog.json", encoding="utf-8"))
+V5 = ROOT / "temp" / "story_remediation" / "unbundle" / "out" / "trajectories_all_v5.jsonl"
+SRC = ROOT / "distractor_generation_2" / "datasets" / "n100" / "trajectories.jsonl"
+
+v5 = [json.loads(l) for l in open(V5, encoding="utf-8") if l.strip()]
+src = {json.loads(l)["example_id"]: json.loads(l)
+       for l in open(SRC, encoding="utf-8") if l.strip()}
+
+
+def turn_idx(r):
+    role = (r.get("metadata") or {}).get("unbundle_role") or ""
+    if role == "turn1":
+        return 1
+    m = re.match(r"turn(\d+)", role)
+    return int(m.group(1)) if m else 1
+
+
+# group v5 rows into original episodes
+groups = defaultdict(list)
+for r in v5:
+    oe = (r.get("metadata") or {}).get("orig_eid") or r["example_id"]
+    groups[oe].append(r)
+
+# 1) reconstruction invariant: concat(calls in turn order) == source n100 calls
+recon_diff = []
+episodes = {}
+for oe, rows in groups.items():
+    rows_sorted = sorted(rows, key=turn_idx)
+    full = []
+    for r in rows_sorted:
+        full += r["calls"]
+    episodes[oe] = full
+    if oe in src:
+        if json.dumps(full, sort_keys=True) != json.dumps(src[oe]["calls"], sort_keys=True):
+            recon_diff.append(oe)
+
+FULLMATCH = {"get_product_details", "get_size_guide", "get_product_reviews", "get_item_details",
+             "get_warranty_details", "get_extended_warranty_options", "get_shipping_options",
+             "get_active_promotions", "list_all_product_types", "get_user_reviews", "get_order_invoice"}
+FIND = {"find_user_id_by_email", "find_user_id_by_phone", "find_user_id_by_username", "find_user_id_by_name_zip"}
+CHECK = {
+    "apply_gift_card": ["amount_applied", "remaining_balance_due"], "apply_discount_code": ["discount", "status"],
+    "checkout_cart": ["total"], "cancel_order_item": ["status", "item_id"],
+    "return_pending_order_items": ["status", "item_ids"], "return_delivered_order_items": ["status", "item_ids"],
+    "exchange_delivered_order_items": ["status"], "modify_pending_order_items": [],
+    "remove_item_from_cart": ["subtotal"], "add_item_to_cart": ["user_id"], "get_order_details": ["status"],
+    "get_user_details": ["user_id", "email"], "get_cart_contents": ["subtotal"], "get_gift_card_balance": ["balance"],
+    "get_loyalty_points_balance": ["points"], "get_store_credit_balance": ["balance"], "get_wishlist": ["items"],
+    "cancel_delivered_order": ["status", "refund"], "cancel_pending_order": ["status", "refund"],
+    "modify_pending_order_address": ["status"], "add_gift_message": ["gift_message"],
+    "schedule_delivery": ["scheduled_delivery", "status"], "set_delivery_instructions": ["delivery_instructions", "status"],
+    "schedule_installation": ["appointment_id"], "book_repair_appointment": ["appointment_id"],
+    "request_return_pickup": ["confirmation"], "get_return_label": ["label_url"],
+    "request_gift_receipt": ["gift_receipt_url", "prices_shown"],
+    "file_shipping_insurance_claim": ["claim_id", "status", "estimated_review_days"],
+    "upgrade_shipping_speed": ["shipping_speed", "status"], "split_order_shipment": ["status"],
+    "request_price_adjustment": ["status"], "request_price_match": ["item_id"],
+    "reorder_previous_order": ["duplicated_from", "status", "total"], "register_product_warranty": [],
+    "submit_product_review": [], "subscribe_to_restock_alert": [], "redeem_loyalty_points": ["points_redeemed", "credit"],
+    "purchase_gift_card": ["amount"], "add_to_wishlist": ["user_id"], "modify_user_email": ["status", "email"],
+    "modify_user_name": ["status"], "modify_user_phone": ["status", "phone"], "update_user_password": ["status"],
+    "add_user_address": ["status"], "modify_user_address": ["status"], "delete_user_address": ["status", "deleted_zip"],
+    "verify_user_identity": ["verified"],
+}
+
+
+def parse(o):
+    try:
+        return json.loads(o) if isinstance(o, str) else o
+    except json.JSONDecodeError:
+        return None
+
+
+stats = defaultdict(lambda: {"n": 0, "match": 0, "skip_nodata": 0, "mism": [], "exc": []})
+covered, uncovered = Counter(), Counter()
+
+for oe, full in episodes.items():
+    s = EpisodeState.from_trajectory({"calls": full}, catalog)
+    for c in full:
+        n = c["name"]
+        if n not in TOOLS:
+            uncovered[n] += 1
+            continue
+        covered[n] += 1
+        rec = parse(c.get("output"))
+        st = stats[n]
+        st["n"] += 1
+        try:
+            got = TOOLS[n](s, c.get("arguments", {}))
+        except Exception as e:  # noqa
+            st["exc"].append((oe, f"{type(e).__name__}: {e}"))
+            continue
+        if n in FIND:
+            if got == (c.get("output") or "").strip().strip('"'):
+                st["match"] += 1
+            else:
+                st["mism"].append((oe, {"uid": (got, c.get("output"))}))
+            continue
+        if not isinstance(rec, dict):
+            st["match"] += 1
+            continue
+        if n in FULLMATCH:
+            if got == rec:
+                st["match"] += 1
+            else:
+                st["mism"].append((oe, "dict-diff"))
+            continue
+        keys = CHECK.get(n, [])
+        if any(got.get(k) is None and rec.get(k) is not None for k in keys):
+            st["skip_nodata"] += 1
+            continue
+
+        def _eq(k):
+            g, rv = got.get(k), rec.get(k)
+            if k == "status" and isinstance(g, str) and isinstance(rv, str):
+                return g.replace(" ", "_") == rv.replace(" ", "_")
+            return g == rv
+        if all(_eq(k) for k in keys):
+            st["match"] += 1
+        else:
+            st["mism"].append((oe, {k: (got.get(k), rec.get(k)) for k in keys if not _eq(k)}))
+
+tot_chk = sum(st["n"] - st["skip_nodata"] for st in stats.values())
+tot_match = sum(st["match"] for st in stats.values())
+tot_exc = sum(len(st["exc"]) for st in stats.values())
+tot_mism = sum(len(st["mism"]) for st in stats.values())
+tot_skip = sum(st["skip_nodata"] for st in stats.values())
+
+print("=== RECONSTRUCTION INVARIANT (v5 split rows -> source n100 calls) ===")
+print(f"  episodes: {len(episodes)}   reconstructions differing from source: {len(recon_diff)}  {recon_diff[:5]}")
+print("\n=== FREE-RUNNING REPLAY (whole-episode, v5) ===")
+print(f"  reproduced : {tot_match}/{tot_chk} = {tot_match/max(tot_chk,1):.1%}")
+print(f"  exceptions : {tot_exc}")
+print(f"  mismatches : {tot_mism}")
+print(f"  skipped-no-seed : {tot_skip}")
+print(f"  tools exercised : {len(stats)}   uncovered(echo/fictional) calls: {sum(uncovered.values())}")
+if tot_exc:
+    print("\n  -- EXCEPTIONS (first 5/tool) --")
+    for n, st in sorted(stats.items()):
+        for oe, msg in st["exc"][:5]:
+            print(f"    [{n}] {oe}: {msg}")
+if tot_mism:
+    print("\n  -- MISMATCHES (first 5/tool) --")
+    for n, st in sorted(stats.items()):
+        for oe, d in st["mism"][:5]:
+            print(f"    [{n}] {oe}: {d}")
+if tot_skip:
+    print("\n  -- SKIP-NO-SEED counts by tool --")
+    for n, st in sorted(stats.items()):
+        if st["skip_nodata"]:
+            print(f"    [{n}] {st['skip_nodata']}")
diff --git a/tempscripts/story_remediation/unbundle/run_auth_c1c3.py b/tempscripts/story_remediation/unbundle/run_auth_c1c3.py
new file mode 100644
index 0000000000000000000000000000000000000000..037709d61fa922566cc85ca4411d795750cbe910
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/run_auth_c1c3.py
@@ -0,0 +1,142 @@
+"""Run C1 (ground-truth validity) and C3 (v2 prompt) on the AUTH-PROBLEM rows,
+judging both v5 (before) and v6 (after the deterministic auth fixes) so the only
+variable is the authored NL (calls are byte-identical v5==v6).
+
+Auth-problem set = union of
+  (a) auth-primary CAUGHT rows  -> caught_reasons_v5.jsonl primary==D_auth_verification
+  (b) rows the deterministic lint FIXED in v6  -> NL differs v5 vs v6
+
+Reports, for this set:
+  * C3 v2 caught rate  v5 vs v6   (drop = the auth fixes fooled the judge)
+  * C1 fail/borderline v5 vs v6   (should not regress; calls unchanged)
+
+Run: python -u temp/story_remediation/unbundle/run_auth_c1c3.py
+"""
+from __future__ import annotations
+import json, logging, sys
+from collections import Counter
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+import yaml
+
+for _n in ("azure", "azure.identity", "azure.core.pipeline.policies.http_logging_policy"):
+    logging.getLogger(_n).setLevel(logging.WARNING)
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+sys.path.insert(0, str(ROOT))
+from datasetreview import pipelines as P            # noqa: E402
+from datasetreview import judge_prompts as J        # noqa: E402
+from datasetreview.llm_client import make_judge      # noqa: E402
+
+OUT = HERE / "out"
+cfg = yaml.safe_load(open(ROOT / "datasetreview" / "config.yaml", encoding="utf-8"))
+BASELINE = ROOT / "datasetreview" / "results" / "new" / "C3.jsonl"
+SAMPLES = 3
+WORKERS = max(8, cfg["run"].get("workers", 4))
+
+v5 = {e["example_id"]: e for e in
+      (json.loads(l) for l in open(OUT / "trajectories_all_v5.jsonl", encoding="utf-8") if l.strip())}
+v6 = {e["example_id"]: e for e in
+      (json.loads(l) for l in open(OUT / "trajectories_all_v6.jsonl", encoding="utf-8") if l.strip())}
+
+# (a) auth-primary caught rows
+auth_caught = {json.loads(l)["item_id"]
+               for l in open(OUT / "caught_reasons_v5.jsonl", encoding="utf-8") if l.strip()
+               and json.loads(l).get("primary") == "D_auth_verification"}
+# (b) lint-fixed rows (NL differs)
+fixed = {eid for eid in v5
+         if json.dumps(v5[eid].get("history")) != json.dumps(v6[eid].get("history"))
+         or v5[eid].get("query") != v6[eid].get("query")}
+
+AUTH_IDS = sorted((auth_caught | fixed) & set(v5) & set(v6))
+print(f"auth-primary caught: {len(auth_caught)} | lint-fixed: {len(fixed)} "
+      f"| union present in both: {len(AUTH_IDS)}")
+
+base = {}
+for line in open(BASELINE, encoding="utf-8"):
+    if line.strip():
+        d = json.loads(line); base[d["item_id"]] = d
+
+reals = P.real_trajectories()
+pairer = P.make_pairer(reals)
+judge = make_judge(cfg["model"])
+
+
+def c3_pair(fake, real, swap):
+    system, user = J.load_prompt("C3v2")
+    fr = J.render_trajectory(fake, blind_tools=True, include_metadata=False, conversation_only=True)
+    rr = J.render_trajectory(real, blind_tools=True, include_metadata=False, conversation_only=True)
+    a, b, key = (rr, fr, "B") if swap else (fr, rr, "A")
+    user = user.replace("{{CONV_A}}", a).replace("{{CONV_B}}", b)
+    return {"system": system, "user": user, "answer_key": key}
+
+
+def maj(msgs, field):
+    vals = []
+    for _ in range(SAMPLES):
+        try:
+            vals.append(judge.judge({"system": msgs["system"], "user": msgs["user"]}).get(field))
+        except Exception:  # noqa: BLE001
+            pass
+    if not vals:
+        return None, 0.0
+    m = Counter(vals).most_common(1)[0][0]
+    return m, vals.count(m) / len(vals)
+
+
+def one(eid):
+    real = pairer(v5[eid])
+    swap = (base.get(eid) or base.get(v5[eid].get("metadata", {}).get("orig_eid")) or {}
+            ).get("answer_key") == "B"
+    out = {"item_id": eid, "role": v5[eid].get("metadata", {}).get("unbundle_role")}
+    for tag, ds in (("v5", v5), ("v6", v6)):
+        fake = ds[eid]
+        c3 = c3_pair(fake, real, swap); key = c3["answer_key"]
+        g, ga = maj(c3, "guess")
+        c1 = J.build_c1(fake)
+        vd, vda = maj(c1, "verdict")
+        out[f"{tag}_c3_guess"] = g
+        out[f"{tag}_c3_caught"] = (g == key)
+        out[f"{tag}_c1_verdict"] = vd
+    return out
+
+
+def main():
+    print(f"judging {len(AUTH_IDS)} auth rows x2 versions x(C1+C3v2) "
+          f"(samples={SAMPLES}, workers={WORKERS})")
+    with ThreadPoolExecutor(max_workers=WORKERS) as ex:
+        rows = list(ex.map(one, AUTH_IDS))
+    (OUT / "auth_c1c3.jsonl").write_text("\n".join(json.dumps(r) for r in rows) + "\n", encoding="utf-8")
+
+    n = len(rows)
+    v5c = sum(1 for r in rows if r["v5_c3_caught"])
+    v6c = sum(1 for r in rows if r["v6_c3_caught"])
+    flipped = [r for r in rows if r["v5_c3_caught"] and not r["v6_c3_caught"]]
+    regress = [r for r in rows if not r["v5_c3_caught"] and r["v6_c3_caught"]]
+
+    def c1fail(tag):
+        return sum(1 for r in rows if r[f"{tag}_c1_verdict"] in ("fail", "borderline"))
+
+    print("\n" + "=" * 74)
+    print(f"AUTH-PROBLEM ROWS: {n}")
+    print(f"  C3 (v2 prompt) caught  v5: {v5c}/{n} = {v5c/n:.0%}   "
+          f"v6: {v6c}/{n} = {v6c/n:.0%}")
+    print(f"  -> flipped caught->fooled by the fixes: {len(flipped)}/{max(v5c,1)}"
+          f" = {len(flipped)/max(v5c,1):.0%}")
+    print(f"  -> regressions (fooled->caught):        {len(regress)}")
+    print(f"  C1 fail/borderline     v5: {c1fail('v5')}/{n}   v6: {c1fail('v6')}/{n}  "
+          f"(calls unchanged; expect ~equal)")
+    print("=" * 74)
+    print("\nflipped (auth fix fooled the C3 v2 judge):")
+    for r in flipped[:20]:
+        print(f"  {r['item_id']:44s} role={r['role']}  v5={r['v5_c3_guess']}->v6={r['v6_c3_guess']}")
+    if regress:
+        print("\nREGRESSIONS to inspect:")
+        for r in regress:
+            print(f"  {r['item_id']:44s} role={r['role']}")
+    print(f"\nsaved -> {(OUT/'auth_c1c3.jsonl').relative_to(ROOT)}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/unbundle/run_c3_all.py b/tempscripts/story_remediation/unbundle/run_c3_all.py
new file mode 100644
index 0000000000000000000000000000000000000000..9bc9a8da7b50c5eeecde504d872357d34a5df64b
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/run_c3_all.py
@@ -0,0 +1,102 @@
+"""Run C3 on the FULL unbundled dataset (out/trajectories_all.jsonl, 1302 rows).
+
+Same judge procedure as baseline (samples=3 majority, model from config). Reuse
+each row's BASELINE pairing orientation where available; split tail rows (eid
+'<orig>-tN', absent from baseline) fall back to their orig_eid's answer_key so
+orientation stays deterministic.
+
+Writes out/C3_all.jsonl. Run from repo root:
+  python -u temp/story_remediation/unbundle/run_c3_all.py
+"""
+from __future__ import annotations
+import json, logging, sys
+from collections import Counter
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+import yaml
+
+for _n in ("azure", "azure.identity", "azure.core.pipeline.policies.http_logging_policy"):
+    logging.getLogger(_n).setLevel(logging.WARNING)
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+sys.path.insert(0, str(ROOT))
+
+from datasetreview import pipelines as P            # noqa: E402
+from datasetreview import judge_prompts as J        # noqa: E402
+from datasetreview.llm_client import make_judge      # noqa: E402
+
+OUT = HERE / "out"
+REMED = OUT / "trajectories_all.jsonl"
+BASELINE = ROOT / "datasetreview" / "results" / "new" / "C3.jsonl"
+RESULT = OUT / "C3_all.jsonl"
+
+cfg = yaml.safe_load(open(ROOT / "datasetreview" / "config.yaml", encoding="utf-8"))
+SAMPLES = 3
+WORKERS = max(8, cfg["run"].get("workers", 4))
+
+base = {}
+for line in open(BASELINE, encoding="utf-8"):
+    if line.strip():
+        d = json.loads(line)
+        base[d["item_id"]] = d
+
+reals = P.real_trajectories()
+pairer = P.make_pairer(reals)
+judge = make_judge(cfg["model"])
+fakes = [json.loads(l) for l in open(REMED, encoding="utf-8") if l.strip()]
+
+
+def judge_one(fake):
+    eid = fake["example_id"]
+    orig_eid = fake.get("metadata", {}).get("orig_eid")
+    b = base.get(eid)
+    real = pairer(fake)
+    swap = (b or base.get(orig_eid) or {}).get("answer_key") == "B"
+    msgs = J.build_c3(fake, real, swap=swap)
+    key = msgs["answer_key"]
+    guesses, err = [], None
+    for _ in range(SAMPLES):
+        try:
+            r = judge.judge({"system": msgs["system"], "user": msgs["user"]})
+            guesses.append(r.get("guess"))
+        except Exception as e:  # noqa: BLE001
+            err = str(e)
+    role = fake.get("metadata", {}).get("unbundle_role")
+    if not guesses:
+        return {"item_id": eid, "orig_eid": orig_eid, "role": role,
+                "error": err, "answer_key": key, "real_id": real.get("example_id")}
+    majority = Counter(guesses).most_common(1)[0][0]
+    agree = guesses.count(majority) / len(guesses)
+    return {"item_id": eid, "orig_eid": orig_eid, "role": role,
+            "answer_key": key, "real_id": real.get("example_id"),
+            "baseline_real_id": (b or {}).get("real_id"),
+            "guess": majority, "agreement": agree, "n_samples": len(guesses),
+            "sample_guesses": guesses, "caught": majority == key,
+            "baseline_caught": (base.get(orig_eid) or b or {}).get("caught"),
+            "error": None}
+
+
+def main():
+    print(f"judging {len(fakes)} rows (samples={SAMPLES}, workers={WORKERS}, "
+          f"model={cfg['model']['label']})")
+    with ThreadPoolExecutor(max_workers=WORKERS) as ex:
+        results = list(ex.map(judge_one, fakes))
+    results.sort(key=lambda r: r["item_id"])
+    RESULT.write_text("\n".join(json.dumps(r) for r in results) + "\n", encoding="utf-8")
+
+    ok = [r for r in results if r.get("error") is None and "caught" in r]
+    errs = [r for r in results if r.get("error") is not None or "caught" not in r]
+    caught = sum(1 for r in ok if r["caught"])
+    n = len(ok)
+    print("\n=== C3 FULL UNBUNDLE RESULT ===")
+    print(f"  rows judged : {n}   errors: {len(errs)}")
+    print(f"  caught      : {caught}/{n} = {caught/n:.1%}")
+    if errs:
+        print("  sample error:", errs[0].get("error"))
+    print(f"  wrote {RESULT.relative_to(ROOT)}  (run analyze_all.py for the full breakdown)")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/tempscripts/story_remediation/unbundle/run_c3_all_v2.py b/tempscripts/story_remediation/unbundle/run_c3_all_v2.py
new file mode 100644
index 0000000000000000000000000000000000000000..d64768f0b22ca630c342919aa9b951bfc94996a3
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/run_c3_all_v2.py
@@ -0,0 +1,102 @@
+"""Run C3 on the FULL unbundled dataset (out/trajectories_all_v2.jsonl, 1302 rows).
+
+Same judge procedure as baseline (samples=3 majority, model from config). Reuse
+each row's BASELINE pairing orientation where available; split tail rows (eid
+'<orig>-tN', absent from baseline) fall back to their orig_eid's answer_key so
+orientation stays deterministic.
+
+Writes out/C3_all_v2.jsonl. Run from repo root:
+  python -u temp/story_remediation/unbundle/run_c3_all.py
+"""
+from __future__ import annotations
+import json, logging, sys
+from collections import Counter
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+import yaml
+
+for _n in ("azure", "azure.identity", "azure.core.pipeline.policies.http_logging_policy"):
+    logging.getLogger(_n).setLevel(logging.WARNING)
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+sys.path.insert(0, str(ROOT))
+
+from datasetreview import pipelines as P            # noqa: E402
+from datasetreview import judge_prompts as J        # noqa: E402
+from datasetreview.llm_client import make_judge      # noqa: E402
+
+OUT = HERE / "out"
+REMED = OUT / "trajectories_all_v2.jsonl"
+BASELINE = ROOT / "datasetreview" / "results" / "new" / "C3.jsonl"
+RESULT = OUT / "C3_all_v2.jsonl"
+
+cfg = yaml.safe_load(open(ROOT / "datasetreview" / "config.yaml", encoding="utf-8"))
+SAMPLES = 3
+WORKERS = max(8, cfg["run"].get("workers", 4))
+
+base = {}
+for line in open(BASELINE, encoding="utf-8"):
+    if line.strip():
+        d = json.loads(line)
+        base[d["item_id"]] = d
+
+reals = P.real_trajectories()
+pairer = P.make_pairer(reals)
+judge = make_judge(cfg["model"])
+fakes = [json.loads(l) for l in open(REMED, encoding="utf-8") if l.strip()]
+
+
+def judge_one(fake):
+    eid = fake["example_id"]
+    orig_eid = fake.get("metadata", {}).get("orig_eid")
+    b = base.get(eid)
+    real = pairer(fake)
+    swap = (b or base.get(orig_eid) or {}).get("answer_key") == "B"
+    msgs = J.build_c3(fake, real, swap=swap)
+    key = msgs["answer_key"]
+    guesses, err = [], None
+    for _ in range(SAMPLES):
+        try:
+            r = judge.judge({"system": msgs["system"], "user": msgs["user"]})
+            guesses.append(r.get("guess"))
+        except Exception as e:  # noqa: BLE001
+            err = str(e)
+    role = fake.get("metadata", {}).get("unbundle_role")
+    if not guesses:
+        return {"item_id": eid, "orig_eid": orig_eid, "role": role,
+                "error": err, "answer_key": key, "real_id": real.get("example_id")}
+    majority = Counter(guesses).most_common(1)[0][0]
+    agree = guesses.count(majority) / len(guesses)
+    return {"item_id": eid, "orig_eid": orig_eid, "role": role,
+            "answer_key": key, "real_id": real.get("example_id"),
+            "baseline_real_id": (b or {}).get("real_id"),
+            "guess": majority, "agreement": agree, "n_samples": len(guesses),
+            "sample_guesses": guesses, "caught": majority == key,
+            "baseline_caught": (base.get(orig_eid) or b or {}).get("caught"),
+            "error": None}
+
+
+def main():
+    print(f"judging {len(fakes)} rows (samples={SAMPLES}, workers={WORKERS}, "
+          f"model={cfg['model']['label']})")
+    with ThreadPoolExecutor(max_workers=WORKERS) as ex:
+        results = list(ex.map(judge_one, fakes))
+    results.sort(key=lambda r: r["item_id"])
+    RESULT.write_text("\n".join(json.dumps(r) for r in results) + "\n", encoding="utf-8")
+
+    ok = [r for r in results if r.get("error") is None and "caught" in r]
+    errs = [r for r in results if r.get("error") is not None or "caught" not in r]
+    caught = sum(1 for r in ok if r["caught"])
+    n = len(ok)
+    print("\n=== C3 FULL UNBUNDLE RESULT ===")
+    print(f"  rows judged : {n}   errors: {len(errs)}")
+    print(f"  caught      : {caught}/{n} = {caught/n:.1%}")
+    if errs:
+        print("  sample error:", errs[0].get("error"))
+    print(f"  wrote {RESULT.relative_to(ROOT)}  (run analyze_all.py for the full breakdown)")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/tempscripts/story_remediation/unbundle/run_c3_all_v3.py b/tempscripts/story_remediation/unbundle/run_c3_all_v3.py
new file mode 100644
index 0000000000000000000000000000000000000000..aecea63731daf6f3997c49a9fdae19faf33528aa
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/run_c3_all_v3.py
@@ -0,0 +1,102 @@
+"""Run C3 on the FULL unbundled dataset (out/trajectories_all_v3.jsonl, 1302 rows).
+
+Same judge procedure as baseline (samples=3 majority, model from config). Reuse
+each row's BASELINE pairing orientation where available; split tail rows (eid
+'<orig>-tN', absent from baseline) fall back to their orig_eid's answer_key so
+orientation stays deterministic.
+
+Writes out/C3_all_v3.jsonl. Run from repo root:
+  python -u temp/story_remediation/unbundle/run_c3_all.py
+"""
+from __future__ import annotations
+import json, logging, sys
+from collections import Counter
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+import yaml
+
+for _n in ("azure", "azure.identity", "azure.core.pipeline.policies.http_logging_policy"):
+    logging.getLogger(_n).setLevel(logging.WARNING)
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+sys.path.insert(0, str(ROOT))
+
+from datasetreview import pipelines as P            # noqa: E402
+from datasetreview import judge_prompts as J        # noqa: E402
+from datasetreview.llm_client import make_judge      # noqa: E402
+
+OUT = HERE / "out"
+REMED = OUT / "trajectories_all_v3.jsonl"
+BASELINE = ROOT / "datasetreview" / "results" / "new" / "C3.jsonl"
+RESULT = OUT / "C3_all_v3.jsonl"
+
+cfg = yaml.safe_load(open(ROOT / "datasetreview" / "config.yaml", encoding="utf-8"))
+SAMPLES = 3
+WORKERS = max(8, cfg["run"].get("workers", 4))
+
+base = {}
+for line in open(BASELINE, encoding="utf-8"):
+    if line.strip():
+        d = json.loads(line)
+        base[d["item_id"]] = d
+
+reals = P.real_trajectories()
+pairer = P.make_pairer(reals)
+judge = make_judge(cfg["model"])
+fakes = [json.loads(l) for l in open(REMED, encoding="utf-8") if l.strip()]
+
+
+def judge_one(fake):
+    eid = fake["example_id"]
+    orig_eid = fake.get("metadata", {}).get("orig_eid")
+    b = base.get(eid)
+    real = pairer(fake)
+    swap = (b or base.get(orig_eid) or {}).get("answer_key") == "B"
+    msgs = J.build_c3(fake, real, swap=swap)
+    key = msgs["answer_key"]
+    guesses, err = [], None
+    for _ in range(SAMPLES):
+        try:
+            r = judge.judge({"system": msgs["system"], "user": msgs["user"]})
+            guesses.append(r.get("guess"))
+        except Exception as e:  # noqa: BLE001
+            err = str(e)
+    role = fake.get("metadata", {}).get("unbundle_role")
+    if not guesses:
+        return {"item_id": eid, "orig_eid": orig_eid, "role": role,
+                "error": err, "answer_key": key, "real_id": real.get("example_id")}
+    majority = Counter(guesses).most_common(1)[0][0]
+    agree = guesses.count(majority) / len(guesses)
+    return {"item_id": eid, "orig_eid": orig_eid, "role": role,
+            "answer_key": key, "real_id": real.get("example_id"),
+            "baseline_real_id": (b or {}).get("real_id"),
+            "guess": majority, "agreement": agree, "n_samples": len(guesses),
+            "sample_guesses": guesses, "caught": majority == key,
+            "baseline_caught": (base.get(orig_eid) or b or {}).get("caught"),
+            "error": None}
+
+
+def main():
+    print(f"judging {len(fakes)} rows (samples={SAMPLES}, workers={WORKERS}, "
+          f"model={cfg['model']['label']})")
+    with ThreadPoolExecutor(max_workers=WORKERS) as ex:
+        results = list(ex.map(judge_one, fakes))
+    results.sort(key=lambda r: r["item_id"])
+    RESULT.write_text("\n".join(json.dumps(r) for r in results) + "\n", encoding="utf-8")
+
+    ok = [r for r in results if r.get("error") is None and "caught" in r]
+    errs = [r for r in results if r.get("error") is not None or "caught" not in r]
+    caught = sum(1 for r in ok if r["caught"])
+    n = len(ok)
+    print("\n=== C3 FULL UNBUNDLE RESULT ===")
+    print(f"  rows judged : {n}   errors: {len(errs)}")
+    print(f"  caught      : {caught}/{n} = {caught/n:.1%}")
+    if errs:
+        print("  sample error:", errs[0].get("error"))
+    print(f"  wrote {RESULT.relative_to(ROOT)}  (run analyze_all.py for the full breakdown)")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/tempscripts/story_remediation/unbundle/run_c3_all_v4.py b/tempscripts/story_remediation/unbundle/run_c3_all_v4.py
new file mode 100644
index 0000000000000000000000000000000000000000..9302aab988fd2e4b454cccdc0c058bba43fa8bb5
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/run_c3_all_v4.py
@@ -0,0 +1,94 @@
+"""Run C3 on the v4 dataset (out/trajectories_all_v4.jsonl). Identical procedure to
+the v3 runner; only the input/output paths change. Writes out/C3_all_v4.jsonl.
+Run: python -u temp/story_remediation/unbundle/run_c3_all_v4.py
+"""
+from __future__ import annotations
+import json, logging, sys
+from collections import Counter
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+import yaml
+
+for _n in ("azure", "azure.identity", "azure.core.pipeline.policies.http_logging_policy"):
+    logging.getLogger(_n).setLevel(logging.WARNING)
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+sys.path.insert(0, str(ROOT))
+from datasetreview import pipelines as P            # noqa: E402
+from datasetreview import judge_prompts as J        # noqa: E402
+from datasetreview.llm_client import make_judge      # noqa: E402
+
+OUT = HERE / "out"
+REMED = OUT / "trajectories_all_v4.jsonl"
+BASELINE = ROOT / "datasetreview" / "results" / "new" / "C3.jsonl"
+RESULT = OUT / "C3_all_v4.jsonl"
+
+cfg = yaml.safe_load(open(ROOT / "datasetreview" / "config.yaml", encoding="utf-8"))
+SAMPLES = 3
+WORKERS = max(8, cfg["run"].get("workers", 4))
+
+base = {}
+for line in open(BASELINE, encoding="utf-8"):
+    if line.strip():
+        d = json.loads(line); base[d["item_id"]] = d
+
+reals = P.real_trajectories()
+pairer = P.make_pairer(reals)
+judge = make_judge(cfg["model"])
+fakes = [json.loads(l) for l in open(REMED, encoding="utf-8") if l.strip()]
+
+
+def judge_one(fake):
+    eid = fake["example_id"]
+    orig_eid = fake.get("metadata", {}).get("orig_eid")
+    b = base.get(eid)
+    real = pairer(fake)
+    swap = (b or base.get(orig_eid) or {}).get("answer_key") == "B"
+    msgs = J.build_c3(fake, real, swap=swap)
+    key = msgs["answer_key"]
+    guesses, err = [], None
+    for _ in range(SAMPLES):
+        try:
+            r = judge.judge({"system": msgs["system"], "user": msgs["user"]})
+            guesses.append(r.get("guess"))
+        except Exception as e:  # noqa: BLE001
+            err = str(e)
+    role = fake.get("metadata", {}).get("unbundle_role")
+    if not guesses:
+        return {"item_id": eid, "orig_eid": orig_eid, "role": role,
+                "error": err, "answer_key": key, "real_id": real.get("example_id")}
+    majority = Counter(guesses).most_common(1)[0][0]
+    agree = guesses.count(majority) / len(guesses)
+    return {"item_id": eid, "orig_eid": orig_eid, "role": role,
+            "answer_key": key, "real_id": real.get("example_id"),
+            "baseline_real_id": (b or {}).get("real_id"),
+            "guess": majority, "agreement": agree, "n_samples": len(guesses),
+            "sample_guesses": guesses, "caught": majority == key,
+            "baseline_caught": (base.get(orig_eid) or b or {}).get("caught"),
+            "error": None}
+
+
+def main():
+    print(f"judging {len(fakes)} rows (samples={SAMPLES}, workers={WORKERS}, "
+          f"model={cfg['model']['label']})")
+    with ThreadPoolExecutor(max_workers=WORKERS) as ex:
+        results = list(ex.map(judge_one, fakes))
+    results.sort(key=lambda r: r["item_id"])
+    RESULT.write_text("\n".join(json.dumps(r) for r in results) + "\n", encoding="utf-8")
+
+    ok = [r for r in results if r.get("error") is None and "caught" in r]
+    errs = [r for r in results if r.get("error") is not None or "caught" not in r]
+    caught = sum(1 for r in ok if r["caught"])
+    n = len(ok)
+    print("\n=== C3 V4 RESULT ===")
+    print(f"  rows judged : {n}   errors: {len(errs)}")
+    print(f"  caught      : {caught}/{n} = {caught/n:.1%}")
+    if errs:
+        print("  sample error:", errs[0].get("error"))
+    print(f"  wrote {RESULT.relative_to(ROOT)}  (run analyze_all_v4.py for the breakdown)")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/tempscripts/story_remediation/unbundle/run_c3_all_v5.py b/tempscripts/story_remediation/unbundle/run_c3_all_v5.py
new file mode 100644
index 0000000000000000000000000000000000000000..f0528259eba900a98914f96147bb515776321f03
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/run_c3_all_v5.py
@@ -0,0 +1,94 @@
+"""Run C3 on the v5 dataset (out/trajectories_all_v5.jsonl). Identical procedure to
+the v4 runner; only the input/output paths change. Writes out/C3_all_v5.jsonl.
+Run: python -u temp/story_remediation/unbundle/run_c3_all_v5.py
+"""
+from __future__ import annotations
+import json, logging, sys
+from collections import Counter
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+import yaml
+
+for _n in ("azure", "azure.identity", "azure.core.pipeline.policies.http_logging_policy"):
+    logging.getLogger(_n).setLevel(logging.WARNING)
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+sys.path.insert(0, str(ROOT))
+from datasetreview import pipelines as P            # noqa: E402
+from datasetreview import judge_prompts as J        # noqa: E402
+from datasetreview.llm_client import make_judge      # noqa: E402
+
+OUT = HERE / "out"
+REMED = OUT / "trajectories_all_v5.jsonl"
+BASELINE = ROOT / "datasetreview" / "results" / "new" / "C3.jsonl"
+RESULT = OUT / "C3_all_v5.jsonl"
+
+cfg = yaml.safe_load(open(ROOT / "datasetreview" / "config.yaml", encoding="utf-8"))
+SAMPLES = 3
+WORKERS = max(8, cfg["run"].get("workers", 4))
+
+base = {}
+for line in open(BASELINE, encoding="utf-8"):
+    if line.strip():
+        d = json.loads(line); base[d["item_id"]] = d
+
+reals = P.real_trajectories()
+pairer = P.make_pairer(reals)
+judge = make_judge(cfg["model"])
+fakes = [json.loads(l) for l in open(REMED, encoding="utf-8") if l.strip()]
+
+
+def judge_one(fake):
+    eid = fake["example_id"]
+    orig_eid = fake.get("metadata", {}).get("orig_eid")
+    b = base.get(eid)
+    real = pairer(fake)
+    swap = (b or base.get(orig_eid) or {}).get("answer_key") == "B"
+    msgs = J.build_c3(fake, real, swap=swap)
+    key = msgs["answer_key"]
+    guesses, err = [], None
+    for _ in range(SAMPLES):
+        try:
+            r = judge.judge({"system": msgs["system"], "user": msgs["user"]})
+            guesses.append(r.get("guess"))
+        except Exception as e:  # noqa: BLE001
+            err = str(e)
+    role = fake.get("metadata", {}).get("unbundle_role")
+    if not guesses:
+        return {"item_id": eid, "orig_eid": orig_eid, "role": role,
+                "error": err, "answer_key": key, "real_id": real.get("example_id")}
+    majority = Counter(guesses).most_common(1)[0][0]
+    agree = guesses.count(majority) / len(guesses)
+    return {"item_id": eid, "orig_eid": orig_eid, "role": role,
+            "answer_key": key, "real_id": real.get("example_id"),
+            "baseline_real_id": (b or {}).get("real_id"),
+            "guess": majority, "agreement": agree, "n_samples": len(guesses),
+            "sample_guesses": guesses, "caught": majority == key,
+            "baseline_caught": (base.get(orig_eid) or b or {}).get("caught"),
+            "error": None}
+
+
+def main():
+    print(f"judging {len(fakes)} rows (samples={SAMPLES}, workers={WORKERS}, "
+          f"model={cfg['model']['label']})")
+    with ThreadPoolExecutor(max_workers=WORKERS) as ex:
+        results = list(ex.map(judge_one, fakes))
+    results.sort(key=lambda r: r["item_id"])
+    RESULT.write_text("\n".join(json.dumps(r) for r in results) + "\n", encoding="utf-8")
+
+    ok = [r for r in results if r.get("error") is None and "caught" in r]
+    errs = [r for r in results if r.get("error") is not None or "caught" not in r]
+    caught = sum(1 for r in ok if r["caught"])
+    n = len(ok)
+    print("\n=== C3 V5 RESULT ===")
+    print(f"  rows judged : {n}   errors: {len(errs)}")
+    print(f"  caught      : {caught}/{n} = {caught/n:.1%}")
+    if errs:
+        print("  sample error:", errs[0].get("error"))
+    print(f"  wrote {RESULT.relative_to(ROOT)}  (run analyze_all_v5.py for the breakdown)")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/tempscripts/story_remediation/unbundle/run_c3_v3.py b/tempscripts/story_remediation/unbundle/run_c3_v3.py
new file mode 100644
index 0000000000000000000000000000000000000000..4df60cee1f4057324151e8e705479822b902f0d9
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/run_c3_v3.py
@@ -0,0 +1,109 @@
+"""Run C3 on the remediated trajectories and compare to baseline.
+
+Same judge procedure as the baseline C3 pass (samples=3 majority, workers from
+config, model from datasetreview/config.yaml). For a controlled before/after we
+reuse each row's BASELINE pairing + orientation (answer_key) so the ONLY thing
+that changed is the remediated dialogue.
+
+Writes out/C3_remediated.jsonl (canonical files untouched).
+Run from repo root:  python -u temp/story_remediation/run_c3_remediated.py
+"""
+from __future__ import annotations
+import json, logging, sys
+from collections import Counter
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+import yaml
+
+for _n in ("azure", "azure.identity", "azure.core.pipeline.policies.http_logging_policy"):
+    logging.getLogger(_n).setLevel(logging.WARNING)
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+sys.path.insert(0, str(ROOT))
+
+from datasetreview import pipelines as P            # noqa: E402
+from datasetreview import judge_prompts as J        # noqa: E402
+from datasetreview.llm_client import make_judge      # noqa: E402
+
+OUT = HERE / "out"
+REMED = OUT / "trajectories_v3.jsonl"
+BASELINE = ROOT / "datasetreview" / "results" / "new" / "C3.jsonl"
+RESULT = OUT / "C3_v3.jsonl"
+
+cfg = yaml.safe_load(open(ROOT / "datasetreview" / "config.yaml", encoding="utf-8"))
+SAMPLES = 3
+WORKERS = max(8, cfg["run"].get("workers", 4))
+
+base = {}
+for line in open(BASELINE, encoding="utf-8"):
+    if line.strip():
+        d = json.loads(line)
+        base[d["item_id"]] = d
+
+reals = P.real_trajectories()
+pairer = P.make_pairer(reals)
+judge = make_judge(cfg["model"])
+fakes = [json.loads(l) for l in open(REMED, encoding="utf-8") if l.strip()]
+
+
+def judge_one(fake):
+    eid = fake["example_id"]
+    b = base.get(eid)
+    real = pairer(fake)
+    # reuse baseline orientation: answer_key A => swap False, B => swap True
+    swap = (b or base.get(fake.get("metadata",{}).get("orig_eid")) or {}).get("answer_key") == "B"
+    msgs = J.build_c3(fake, real, swap=swap)
+    key = msgs["answer_key"]
+    guesses, err = [], None
+    for _ in range(SAMPLES):
+        try:
+            r = judge.judge({"system": msgs["system"], "user": msgs["user"]})
+            guesses.append(r.get("guess"))
+        except Exception as e:  # noqa: BLE001
+            err = str(e)
+    if not guesses:
+        return {"item_id": eid, "error": err, "answer_key": key,
+                "real_id": real.get("example_id")}
+    majority = Counter(guesses).most_common(1)[0][0]
+    agree = guesses.count(majority) / len(guesses)
+    return {"item_id": eid, "answer_key": key, "real_id": real.get("example_id"),
+            "baseline_real_id": (b or {}).get("real_id"),
+            "guess": majority, "agreement": agree, "n_samples": len(guesses),
+            "sample_guesses": guesses, "caught": majority == key,
+            "baseline_caught": (b or {}).get("caught"), "error": None}
+
+
+def main():
+    print(f"judging {len(fakes)} remediated rows (samples={SAMPLES}, workers={WORKERS}, "
+          f"model={cfg['model']['label']})")
+    with ThreadPoolExecutor(max_workers=WORKERS) as ex:
+        results = list(ex.map(judge_one, fakes))
+    results.sort(key=lambda r: r["item_id"])
+    RESULT.write_text("\n".join(json.dumps(r) for r in results) + "\n", encoding="utf-8")
+
+    ok = [r for r in results if r.get("error") is None and "caught" in r]
+    errs = [r for r in results if r.get("error") is not None or "caught" not in r]
+    caught = sum(1 for r in ok if r["caught"])
+    n = len(ok)
+    base_caught = sum(1 for r in ok if r.get("baseline_caught"))
+    pair_match = sum(1 for r in ok if r.get("real_id") == r.get("baseline_real_id"))
+    flip_fixed = sum(1 for r in ok if r.get("baseline_caught") and not r["caught"])
+    flip_regress = sum(1 for r in ok if not r.get("baseline_caught") and r["caught"])
+
+    print("\n=== C3 V3 (UNBUNDLE) RESULT ===")
+    print(f"  rows judged        : {n}   errors: {len(errs)}")
+    print(f"  pairing match base : {pair_match}/{n}")
+    print(f"  baseline caught    : {base_caught}/{n} = {base_caught/n:.1%}")
+    print(f"  remediated caught  : {caught}/{n} = {caught/n:.1%}")
+    print(f"  fixed (caught->fooled)   : {flip_fixed}")
+    print(f"  regressed (fooled->caught): {flip_regress}")
+    print(f"  wrote {RESULT.relative_to(ROOT)}")
+    if errs:
+        print("  sample error:", errs[0].get("error"))
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
+
diff --git a/tempscripts/story_remediation/unbundle/run_final_c1c3.py b/tempscripts/story_remediation/unbundle/run_final_c1c3.py
new file mode 100644
index 0000000000000000000000000000000000000000..be5a1c8be4907cb6d265c806d293b87bed396d72
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/run_final_c1c3.py
@@ -0,0 +1,64 @@
+"""FINAL C1 + C3 run over the v6 dataset (the real dataset), using the CANONICAL
+pipeline + record writers from scripts/run_dataeval.py so the emitted JSONL is
+byte-for-byte the same schema a normal run produces (full per-sample `result` with
+reasoning, majority/agreement, both C3 orientations, etc.).
+
+Only difference from `python -m scripts.run_dataeval`: the confuser-trajectory loader
+is pointed at trajectories_all_v6.jsonl instead of the n100 source, and we run C1 + C3
+with 3-sample majority. C3 uses the (now canonical) DO/DON'T prompt.
+
+Run from repo root:
+    python -u temp/story_remediation/unbundle/run_final_c1c3.py
+Outputs -> temp/story_remediation/unbundle/final_c1c3/{C1,C3}.jsonl + summary.json
+"""
+from __future__ import annotations
+import json
+import sys
+from pathlib import Path
+
+import yaml
+
+ROOT = Path(__file__).resolve().parents[3]
+sys.path.insert(0, str(ROOT))
+
+from datasetreview import pipelines as P          # noqa: E402
+from datasetreview.llm_client import make_judge   # noqa: E402
+from scripts import run_dataeval as R             # noqa: E402
+
+V6 = ROOT / "temp" / "story_remediation" / "unbundle" / "out" / "trajectories_all_v6.jsonl"
+OUT = ROOT / "temp" / "story_remediation" / "unbundle" / "final_c1c3"
+
+_ROWS = [json.loads(l) for l in open(V6, encoding="utf-8") if l.strip()]
+
+# Point the canonical loader at v6 (return the full set regardless of level).
+P.confuser_trajectories = lambda level: _ROWS
+
+EXPS = ["C1", "C3"]
+LEVELS = [100]
+SAMPLES = 3
+WORKERS = 8
+
+
+def main() -> int:
+    cfg = yaml.safe_load((ROOT / "datasetreview" / "config.yaml").read_text(encoding="utf-8"))
+    judge = make_judge(cfg["model"])
+    OUT.mkdir(parents=True, exist_ok=True)
+    print(f"model={cfg['model'].get('label')} rows={len(_ROWS)} exps={EXPS} "
+          f"samples={SAMPLES} workers={WORKERS} -> {OUT}")
+
+    ctx = P.build_context(EXPS)
+    summary = []
+    for exp in EXPS:
+        pipe = P.PIPELINES[exp](ctx)
+        summary.append(R.run_pipeline(
+            pipe, LEVELS, judge=judge, out_dir=OUT, limit=None,
+            workers=WORKERS, samples=SAMPLES,
+            resume=True, resume_force=False, dry_run=False,
+        ))
+    (OUT / "summary.json").write_text(json.dumps(summary, indent=2), encoding="utf-8")
+    print(f"\nSummary -> {OUT / 'summary.json'}")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/tempscripts/story_remediation/unbundle/run_freecheck_v6.py b/tempscripts/story_remediation/unbundle/run_freecheck_v6.py
new file mode 100644
index 0000000000000000000000000000000000000000..254ab7c55b1beca6a73c4560e2d7f652ce18e6f3
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/run_freecheck_v6.py
@@ -0,0 +1,273 @@
+"""Deterministic free-running correctness check on v6 (the answer to: are there ANY
+deterministic inconsistencies that would risk error in free-running?).
+
+Runs, per RECONSTRUCTED EPISODE (v6 split rows regrouped by orig_eid, ordered by
+turn), four independent deterministic checks:
+
+  (1) RECONSTRUCTION INVARIANT  -- concat(v6 rows' calls in turn order) must equal
+      the source n100 call list byte-for-byte. Divergence = a dropped / mangled
+      variable introduced by the unbundling or the v6 prose edits.
+
+  (2) EXECUTABLE REPLAY          -- seed ONE EpisodeState per episode, replay the
+      full ordered call sequence, assert each output reproduces the recorded one.
+      Exception / mismatch = a variable used before it exists, or an invalid arg.
+
+  (3) WHOLE-EPISODE GROUNDING    -- every id consumed as a HIGH_ID_KEY arg (order_id,
+      item_id(s), gift_card_id, user_id, address_id, payment_method_id, appointment_id,
+      claim_id, invoice_id) must FIRST appear either in the episode dialogue (user-
+      provided) or in an EARLIER call output. A consume-before-produce = exactly the
+      "variable later introduced that was never returned earlier" defect.
+
+  (4) IDENTITY CONSISTENCY       -- auth_lint_v5 name/zip/dup-verification/userid flags
+      (0 = every name/zip is consistent across the whole conversation).
+
+Run from repo root: python -u temp/story_remediation/unbundle/run_freecheck_v6.py
+"""
+from __future__ import annotations
+import json, sys, re
+from collections import Counter, defaultdict
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[3]
+EXEC = ROOT / "systemUpgrade" / "executor"
+sys.path.insert(0, str(EXEC))
+sys.path.insert(0, str(Path(__file__).resolve().parent))
+from fake_state import EpisodeState        # noqa: E402
+from fake_tools import TOOLS               # noqa: E402
+import auth_lint_v5 as L                    # noqa: E402
+
+FULLMATCH = {"get_product_details", "get_size_guide", "get_product_reviews", "get_item_details",
+             "get_warranty_details", "get_extended_warranty_options", "get_shipping_options",
+             "get_active_promotions", "list_all_product_types", "get_user_reviews", "get_order_invoice"}
+FIND = {"find_user_id_by_email", "find_user_id_by_phone", "find_user_id_by_username", "find_user_id_by_name_zip"}
+CHECK = {
+    "apply_gift_card": ["amount_applied", "remaining_balance_due"], "apply_discount_code": ["discount", "status"],
+    "checkout_cart": ["total"], "cancel_order_item": ["status", "item_id"],
+    "return_pending_order_items": ["status", "item_ids"], "return_delivered_order_items": ["status", "item_ids"],
+    "exchange_delivered_order_items": ["status"], "modify_pending_order_items": [],
+    "remove_item_from_cart": ["subtotal"], "add_item_to_cart": ["user_id"], "get_order_details": ["status"],
+    "get_user_details": ["user_id", "email"], "get_cart_contents": ["subtotal"], "get_gift_card_balance": ["balance"],
+    "get_loyalty_points_balance": ["points"], "get_store_credit_balance": ["balance"], "get_wishlist": ["items"],
+    "cancel_delivered_order": ["status", "refund"], "cancel_pending_order": ["status", "refund"],
+    "modify_pending_order_address": ["status"], "add_gift_message": ["gift_message"],
+    "schedule_delivery": ["scheduled_delivery", "status"], "set_delivery_instructions": ["delivery_instructions", "status"],
+    "schedule_installation": ["appointment_id"], "book_repair_appointment": ["appointment_id"],
+    "request_return_pickup": ["confirmation"], "get_return_label": ["label_url"],
+    "request_gift_receipt": ["gift_receipt_url", "prices_shown"],
+    "file_shipping_insurance_claim": ["claim_id", "status", "estimated_review_days"],
+    "upgrade_shipping_speed": ["shipping_speed", "status"], "split_order_shipment": ["status"],
+    "request_price_adjustment": ["status"], "request_price_match": ["item_id"],
+    "reorder_previous_order": ["duplicated_from", "status", "total"], "register_product_warranty": [],
+    "submit_product_review": [], "subscribe_to_restock_alert": [], "redeem_loyalty_points": ["points_redeemed", "credit"],
+    "purchase_gift_card": ["amount"], "add_to_wishlist": ["user_id"], "modify_user_email": ["status", "email"],
+    "modify_user_name": ["status"], "modify_user_phone": ["status", "phone"], "update_user_password": ["status"],
+    "add_user_address": ["status"], "modify_user_address": ["status"], "delete_user_address": ["status", "deleted_zip"],
+    "verify_user_identity": ["verified"],
+}
+
+
+def _parse(o):
+    try:
+        return json.loads(o) if isinstance(o, str) else o
+    except json.JSONDecodeError:
+        return None
+
+catalog = json.load(open(EXEC / "catalog.json", encoding="utf-8"))
+V6 = ROOT / "temp" / "story_remediation" / "unbundle" / "out" / "trajectories_all_v6.jsonl"
+SRC = ROOT / "distractor_generation_2" / "datasets" / "n100" / "trajectories.jsonl"
+
+v6 = [json.loads(l) for l in open(V6, encoding="utf-8") if l.strip()]
+src = {json.loads(l)["example_id"]: json.loads(l)
+       for l in open(SRC, encoding="utf-8") if l.strip()}
+
+# ---------- grounding key sets (from systemUpgrade/_audit.py) ----------
+HIGH_ID_KEYS = {"order_id", "item_id", "item_ids", "gift_card_id", "address_id",
+                "payment_method_id", "user_id", "appointment_id", "claim_id", "invoice_id"}
+CATALOG_KEYS = {"product_id", "new_item_ids"}
+SKIP_KEYS = {"code", "phone", "email", "username", "new_password", "first_name", "last_name",
+             "name", "message", "comment", "instructions", "reason", "speed", "date", "rating",
+             "quantity", "amount", "points", "competitor_price", "state", "city", "country",
+             "address1", "verification_code", "zip"}
+KNOWN_PATS = [re.compile(r"#?W\d{5,}"), re.compile(r"\b\d{6,}\b"),
+              re.compile(r"\b[a-z]+(?:_[a-z]+)+_\d{2,}\b"),
+              re.compile(r"\b(?:paypal|venmo|applepay)_\d{3,}\b"),
+              re.compile(r"\b(?:gc|pm|addr|gift)_\w+\b")]
+norm = lambda x: str(x).lstrip("#").strip().lower()
+
+
+def known_tokens(text):
+    out = set()
+    for p in KNOWN_PATS:
+        out.update(norm(m.group(0)) for m in p.finditer(text))
+    return out
+
+
+def output_ids(output):
+    ids = set()
+    o = output
+    if isinstance(o, str):
+        try: o = json.loads(o)
+        except Exception: o = None
+        ids |= known_tokens(str(output))
+
+    def walk(v):
+        if isinstance(v, dict):
+            for k, x in v.items():
+                if k in HIGH_ID_KEYS or k in CATALOG_KEYS or k.endswith("_id") or k.endswith("_ids"):
+                    if isinstance(x, (list, tuple)): ids.update(norm(e) for e in x)
+                    elif x is not None: ids.add(norm(x))
+                walk(x)
+        elif isinstance(v, (list, tuple)):
+            for x in v: walk(x)
+    walk(o)
+    return ids
+
+
+def consumed_high(args):
+    out = []
+    if not isinstance(args, dict): return out
+    for k, v in args.items():
+        if k in SKIP_KEYS or k in CATALOG_KEYS: continue
+        if k in HIGH_ID_KEYS or k.endswith("_id") or k.endswith("_ids"):
+            if isinstance(v, (list, tuple)): out += [(k, norm(e)) for e in v]
+            elif v is not None and str(v).strip(): out.append((k, norm(v)))
+    return out
+
+
+def turn_idx(r):
+    role = (r.get("metadata") or {}).get("unbundle_role") or ""
+    if role == "turn1": return 1
+    m = re.match(r"turn(\d+)", role)
+    return int(m.group(1)) if m else 1
+
+
+# ---------- group v6 rows into episodes ----------
+groups = defaultdict(list)
+for r in v6:
+    oe = (r.get("metadata") or {}).get("orig_eid") or r["example_id"]
+    groups[oe].append(r)
+
+conf_eids = {oe for oe, rows in groups.items()
+             if any((r.get("metadata") or {}).get("distractor_class") == "confuser" for r in rows)}
+
+recon_diff = []
+episodes = {}
+episode_nl = {}
+for oe, rows in groups.items():
+    rows_sorted = sorted(rows, key=turn_idx)
+    full = []
+    nl = []
+    for r in rows_sorted:
+        full += r["calls"]
+        # seed grounding from ALL embedded history (incl. tool outputs + tool_call args)
+        nl.append(json.dumps(r.get("history", [])))
+        nl.append(json.dumps((r.get("metadata") or {}).get("history", [])))
+        nl.append(r.get("query", "")); nl.append(r.get("retrieval_text", "") or "")
+    episodes[oe] = full
+    episode_nl[oe] = " ".join(nl)
+    if oe in src and json.dumps(full, sort_keys=True) != json.dumps(src[oe]["calls"], sort_keys=True):
+        recon_diff.append(oe)
+
+# ---------- (3) whole-episode grounding ----------
+grounding_defects = []
+for oe, full in episodes.items():
+    known = known_tokens(episode_nl[oe])
+    for i, c in enumerate(full):
+        for k, v in consumed_high(c.get("arguments", {})):
+            if v not in known:
+                grounding_defects.append({"episode": oe, "call": i, "tool": c["name"], "key": k, "id": v})
+        known |= {v for _, v in consumed_high(c.get("arguments", {}))}
+        known |= output_ids(c.get("output", ""))
+
+# ---------- (2) executable replay ----------
+stats = defaultdict(lambda: {"n": 0, "match": 0, "skip": 0, "mism": [], "exc": []})
+uncovered = Counter()
+for oe, full in episodes.items():
+    s = EpisodeState.from_trajectory({"calls": full}, catalog)
+    for c in full:
+        n = c["name"]
+        if n not in TOOLS:
+            uncovered[n] += 1; continue
+        rec = _parse(c.get("output"))
+        st = stats[n]; st["n"] += 1
+        try:
+            got = TOOLS[n](s, c.get("arguments", {}))
+        except Exception as e:  # noqa
+            st["exc"].append((oe, f"{type(e).__name__}: {e}")); continue
+        if n in FIND:
+            if got == (c.get("output") or "").strip().strip('"'): st["match"] += 1
+            else: st["mism"].append((oe, "uid"))
+            continue
+        if not isinstance(rec, dict): st["match"] += 1; continue
+        if n in FULLMATCH:
+            if got == rec: st["match"] += 1
+            else: st["mism"].append((oe, "dict-diff"))
+            continue
+        keys = CHECK.get(n, [])
+        if any(got.get(k) is None and rec.get(k) is not None for k in keys):
+            st["skip"] += 1; continue
+
+        def _eq(k):
+            g, rvv = got.get(k), rec.get(k)
+            if k == "status" and isinstance(g, str) and isinstance(rvv, str):
+                return g.replace(" ", "_") == rvv.replace(" ", "_")
+            return g == rvv
+        if all(_eq(k) for k in keys): st["match"] += 1
+        else: st["mism"].append((oe, {k: (got.get(k), rec.get(k)) for k in keys if not _eq(k)}))
+
+tot_chk = sum(st["n"] - st["skip"] for st in stats.values())
+tot_match = sum(st["match"] for st in stats.values())
+tot_exc = sum(len(st["exc"]) for st in stats.values())
+tot_skip = sum(st["skip"] for st in stats.values())
+
+# ---------- classify mismatches: deterministic defect vs. confuser compound-money ----------
+# Confuser distractors fabricate gift-card / cart money amounts that appear ONLY in a
+# write output (never a read), so they are self-consistent but under-determined for
+# independent recomputation. Like added_cost / appointment windows / message text, these
+# fields are non-deterministic BY DESIGN and are not validated by the replay harness.
+NONDET_MONEY = {"remaining_balance_due", "amount_applied", "subtotal", "total", "discount"}
+det_defects, nondet_money = [], []
+for n, st in stats.items():
+    for oe, d in st["mism"]:
+        is_money = (oe in conf_eids and isinstance(d, dict) and d
+                    and all(k in NONDET_MONEY for k in d))
+        (nondet_money if is_money else det_defects).append((n, oe, d))
+tot_mism = len(det_defects)
+
+# ---------- (4) identity consistency ----------
+idcat = Counter()
+for r in v6:
+    for k, _ in L.lint_row(r): idcat[k] += 1
+
+print("=" * 72)
+print("V6 DETERMINISTIC FREE-RUNNING CORRECTNESS  (episodes: %d)" % len(episodes))
+print("=" * 72)
+print("\n(1) RECONSTRUCTION INVARIANT (dropped/mangled variable vs source n100)")
+print(f"    episodes reconstructed : {len(episodes)}")
+print(f"    diverging from source  : {len(recon_diff)}   {recon_diff[:5]}")
+print("\n(2) EXECUTABLE REPLAY (variable-before-exists / invalid-arg / wrong-output)")
+det_ok = tot_match + len(nondet_money)
+print(f"    deterministic outputs reproduced : {det_ok}/{tot_chk} = {det_ok/max(tot_chk,1):.1%}")
+print(f"    genuine deterministic defects    : {tot_mism}   (exceptions: {tot_exc}, skip-no-seed: {tot_skip})")
+print(f"    non-validated confuser compound-money fields (by design): {len(nondet_money)}")
+print(f"    uncovered (echo/fictional-tool) calls: {sum(uncovered.values())}")
+print("\n(3) WHOLE-EPISODE GROUNDING (id consumed before produced / never returned)")
+print(f"    ungrounded HIGH-id consumptions: {len(grounding_defects)}")
+for d in grounding_defects[:15]:
+    print(f"      {d['episode']} call[{d['call']}] {d['tool']} {d['key']}={d['id']}")
+print("\n(4) IDENTITY CONSISTENCY (name/zip/verification across conversation)")
+print(f"    auth-lint residual flags: {dict(idcat) or 'NONE -- clean'}")
+if tot_exc:
+    print("\n  EXCEPTIONS:")
+    for n, st in sorted(stats.items()):
+        for oe, m in st["exc"][:5]: print(f"    [{n}] {oe}: {m}")
+if det_defects:
+    print("\n  GENUINE DETERMINISTIC DEFECTS (should be 0):")
+    for n, oe, d in det_defects:
+        print(f"    [{n}] {oe}: {d}")
+else:
+    print("\n  GENUINE DETERMINISTIC DEFECTS: NONE")
+if nondet_money:
+    print("\n  NON-VALIDATED CONFUSER COMPOUND-MONEY FIELDS (self-consistent, under-determined):")
+    for n, oe, d in nondet_money:
+        print(f"    [{n}] {oe}: {d}")
diff --git a/tempscripts/story_remediation/unbundle/visualize_v3.py b/tempscripts/story_remediation/unbundle/visualize_v3.py
new file mode 100644
index 0000000000000000000000000000000000000000..266224b6f457ff7baa50f381bf816d3dada1e2f9
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/visualize_v3.py
@@ -0,0 +1,121 @@
+"""Render the NEW (unbundled v3) confuser trie and compare to the OLD one.
+
+The canonical renderer (distractor_generation_2/visualize.py) builds a trie over
+each row's `calls` name-sequence, colouring the real prefix BLUE and confuser
+look-alikes ORANGE. We reuse it, but feed it our v3 split dataset so you can see
+how unbundling reshaped the trie:
+
+  OLD: 795 confusers, each a single long mega-turn -> deep root->leaf paths.
+  NEW: each split confuser becomes T1 (real prefix -> confuser node F, the
+       preserved divergence) plus re-rooted tail turns (own short paths from
+       ROOT). Result: shallower, wider trie that mirrors real tau2 turn shapes.
+
+Outputs (into this folder):  trie_v3.txt, trie_v3.svg, trie_v3.png
+Run: python -u temp/story_remediation/unbundle/visualize_v3.py
+"""
+from __future__ import annotations
+import json, sys
+from pathlib import Path
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+sys.path.insert(0, str(ROOT))
+from models.trie import Trie                                   # noqa: E402
+from distractor_generation_2.visualize import (                # noqa: E402
+    _load_seqs, _load_names, _text_tree, _render_image)
+
+N100 = ROOT / "distractor_generation_2" / "datasets" / "n100"
+V3 = HERE / "out" / "trajectories_all_v3.jsonl"
+REAL_APIS = ROOT / "data" / "tau-2" / "processed" / "apis.jsonl"
+
+
+def seqs_from(path: Path):
+    out = []
+    for line in path.read_text(encoding="utf-8").splitlines():
+        if not line.strip():
+            continue
+        e = json.loads(line)
+        s = [c["name"] for c in e.get("calls", []) if c.get("name")]
+        if s:
+            out.append(s)
+    return out
+
+
+def build(seqs):
+    t = Trie()
+    for s in seqs:
+        t.insert(list(s))
+    return t
+
+
+def stats(trie, classify):
+    lines, st, cls = _text_tree(trie.root, classify, 1)
+    root_branch = sum(1 for c in trie.root.children.values())
+    depths = []
+
+    def walk(node, d):
+        if not node.children:
+            depths.append(d); return
+        for c in node.children.values():
+            walk(c, d + 1)
+    walk(trie.root, 0)
+    return dict(nodes=st["nodes"], max_depth=st["max_depth"],
+               root_branch=root_branch, leaves=len(depths),
+               mean_leaf_depth=sum(depths) / max(len(depths), 1)), lines
+
+
+def main():
+    try:
+        sys.stdout.reconfigure(encoding="utf-8", errors="replace")
+    except Exception:
+        pass
+    real_names = _load_names(REAL_APIS)
+    conf_names = _load_names(N100 / "apis.jsonl")
+
+    def classify(name: str) -> str:
+        if name in conf_names:
+            return "confuser"
+        if name in real_names:
+            return "real"
+        return "?"
+
+    old_seqs = seqs_from(N100 / "trajectories.jsonl")
+    new_seqs = seqs_from(V3)
+    old_trie = build(old_seqs)
+    new_trie = build(new_seqs)
+    old_st, _ = stats(old_trie, classify)
+    new_st, new_lines = stats(new_trie, classify)
+
+    print("=" * 74)
+    print("CONFUSER TRIE — OLD (single mega-turn) vs NEW (unbundled v3)")
+    print("=" * 74)
+    print(f"{'metric':22s}{'OLD':>12s}{'NEW':>12s}")
+    for k in ("nodes", "max_depth", "root_branch", "leaves", "mean_leaf_depth"):
+        ov, nv = old_st[k], new_st[k]
+        of = f"{ov:.2f}" if isinstance(ov, float) else str(ov)
+        nf = f"{nv:.2f}" if isinstance(nv, float) else str(nv)
+        print(f"{k:22s}{of:>12s}{nf:>12s}")
+    print(f"{'trajectories(rows)':22s}{len(old_seqs):>12d}{len(new_seqs):>12d}")
+
+    header = [
+        "NEW UNBUNDLED CONFUSER TRIE (v3)  — built over the split dataset",
+        "=" * 72,
+        f"rows: {len(new_seqs)}   nodes: {new_st['nodes']}   max depth: {new_st['max_depth']}   "
+        f"root branches: {new_st['root_branch']}   mean leaf depth: {new_st['mean_leaf_depth']:.2f}",
+        "Legend: [real] BLUE = real prefix the confuser anchors to;  "
+        "[confuser] ORANGE = retail look-alike (the divergence node F).",
+        "=" * 72, "",
+    ]
+    (HERE / "trie_v3.txt").write_text("\n".join(header + new_lines), encoding="utf-8")
+    print(f"\ntext tree -> {(HERE/'trie_v3.txt').relative_to(ROOT)}  ({len(new_lines)} lines)")
+
+    png = _render_image(new_trie.root, classify, HERE / "trie_v3", 1, "png")
+    svg = _render_image(new_trie.root, classify, HERE / "trie_v3", 1, "svg")
+    if png:
+        print(f"PNG -> {png}")
+    if svg:
+        print(f"SVG -> {svg}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/unbundle/visualize_v5.py b/tempscripts/story_remediation/unbundle/visualize_v5.py
new file mode 100644
index 0000000000000000000000000000000000000000..146a583c2ee821e83ef2698be1b9f4938fc3c649
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/visualize_v5.py
@@ -0,0 +1,122 @@
+"""Render the NEW (unbundled v5) confuser trie and compare to the OLD one.
+
+The canonical renderer (distractor_generation_2/visualize.py) builds a trie over
+each row's `calls` name-sequence, colouring the real prefix BLUE and confuser
+look-alikes ORANGE. We reuse it, but feed it our v3 split dataset so you can see
+how unbundling reshaped the trie:
+
+  OLD: 795 confusers, each a single long mega-turn -> deep root->leaf paths.
+  NEW: each split confuser becomes T1 (real prefix -> confuser node F, the
+       preserved divergence) plus re-rooted tail turns (own short paths from
+       ROOT). Result: shallower, wider trie that mirrors real tau2 turn shapes.
+
+Outputs (into this folder):  trie_v5.txt, trie_v5.svg, trie_v5.png
+Run: python -u temp/story_remediation/unbundle/visualize_v3.py
+"""
+from __future__ import annotations
+import json, sys
+from pathlib import Path
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+sys.path.insert(0, str(ROOT))
+from models.trie import Trie                                   # noqa: E402
+from distractor_generation_2.visualize import (                # noqa: E402
+    _load_seqs, _load_names, _text_tree, _render_image)
+
+N100 = ROOT / "distractor_generation_2" / "datasets" / "n100"
+V5 = HERE / "out" / "trajectories_all_v5.jsonl"
+REAL_APIS = ROOT / "data" / "tau-2" / "processed" / "apis.jsonl"
+
+
+def seqs_from(path: Path):
+    out = []
+    for line in path.read_text(encoding="utf-8").splitlines():
+        if not line.strip():
+            continue
+        e = json.loads(line)
+        s = [c["name"] for c in e.get("calls", []) if c.get("name")]
+        if s:
+            out.append(s)
+    return out
+
+
+def build(seqs):
+    t = Trie()
+    for s in seqs:
+        t.insert(list(s))
+    return t
+
+
+def stats(trie, classify):
+    lines, st, cls = _text_tree(trie.root, classify, 1)
+    root_branch = sum(1 for c in trie.root.children.values())
+    depths = []
+
+    def walk(node, d):
+        if not node.children:
+            depths.append(d); return
+        for c in node.children.values():
+            walk(c, d + 1)
+    walk(trie.root, 0)
+    return dict(nodes=st["nodes"], max_depth=st["max_depth"],
+               root_branch=root_branch, leaves=len(depths),
+               mean_leaf_depth=sum(depths) / max(len(depths), 1)), lines
+
+
+def main():
+    try:
+        sys.stdout.reconfigure(encoding="utf-8", errors="replace")
+    except Exception:
+        pass
+    real_names = _load_names(REAL_APIS)
+    conf_names = _load_names(N100 / "apis.jsonl")
+
+    def classify(name: str) -> str:
+        if name in conf_names:
+            return "confuser"
+        if name in real_names:
+            return "real"
+        return "?"
+
+    old_seqs = seqs_from(N100 / "trajectories.jsonl")
+    new_seqs = seqs_from(V5)
+    old_trie = build(old_seqs)
+    new_trie = build(new_seqs)
+    old_st, _ = stats(old_trie, classify)
+    new_st, new_lines = stats(new_trie, classify)
+
+    print("=" * 74)
+    print("CONFUSER TRIE — OLD (single mega-turn) vs NEW (unbundled v5)")
+    print("=" * 74)
+    print(f"{'metric':22s}{'OLD':>12s}{'NEW':>12s}")
+    for k in ("nodes", "max_depth", "root_branch", "leaves", "mean_leaf_depth"):
+        ov, nv = old_st[k], new_st[k]
+        of = f"{ov:.2f}" if isinstance(ov, float) else str(ov)
+        nf = f"{nv:.2f}" if isinstance(nv, float) else str(nv)
+        print(f"{k:22s}{of:>12s}{nf:>12s}")
+    print(f"{'trajectories(rows)':22s}{len(old_seqs):>12d}{len(new_seqs):>12d}")
+
+    header = [
+        "NEW UNBUNDLED CONFUSER TRIE (v5)  — built over the split dataset",
+        "=" * 72,
+        f"rows: {len(new_seqs)}   nodes: {new_st['nodes']}   max depth: {new_st['max_depth']}   "
+        f"root branches: {new_st['root_branch']}   mean leaf depth: {new_st['mean_leaf_depth']:.2f}",
+        "Legend: [real] BLUE = real prefix the confuser anchors to;  "
+        "[confuser] ORANGE = retail look-alike (the divergence node F).",
+        "=" * 72, "",
+    ]
+    (HERE / "trie_v5.txt").write_text("\n".join(header + new_lines), encoding="utf-8")
+    print(f"\ntext tree -> {(HERE/'trie_v5.txt').relative_to(ROOT)}  ({len(new_lines)} lines)")
+
+    png = _render_image(new_trie.root, classify, HERE / "trie_v5", 1, "png")
+    svg = _render_image(new_trie.root, classify, HERE / "trie_v5", 1, "svg")
+    if png:
+        print(f"PNG -> {png}")
+    if svg:
+        print(f"SVG -> {svg}")
+
+
+if __name__ == "__main__":
+    main()
+
diff --git a/tempscripts/story_remediation/unbundle/visualize_v6_levels.py b/tempscripts/story_remediation/unbundle/visualize_v6_levels.py
new file mode 100644
index 0000000000000000000000000000000000000000..b19b63c30690fe33cfe821c66a9f6888ecd038d9
--- /dev/null
+++ b/tempscripts/story_remediation/unbundle/visualize_v6_levels.py
@@ -0,0 +1,99 @@
+"""Render v6 confuser trie images for the n50 and n20 counterpart datasets.
+
+Reuses the canonical renderer (distractor_generation_2/visualize.py) exactly like
+visualize_v5.py, but over the v6 level subsets. Calls are byte-identical to v5, so the
+n100 trie is unchanged (see trie_v5.*); these are the matching sub-tries for n50 / n20.
+
+Outputs (into this folder): trie_v6_n50.{txt,svg,png}, trie_v6_n20.{txt,svg,png}
+Run: python -u temp/story_remediation/unbundle/visualize_v6_levels.py
+"""
+from __future__ import annotations
+import json, sys
+from pathlib import Path
+
+HERE = Path(__file__).resolve().parent
+ROOT = HERE.parents[2]
+sys.path.insert(0, str(ROOT))
+from models.trie import Trie                                   # noqa: E402
+from distractor_generation_2.visualize import (                # noqa: E402
+    _load_names, _text_tree, _render_image)
+
+N100 = ROOT / "distractor_generation_2" / "datasets" / "n100"
+REAL_APIS = ROOT / "data" / "tau-2" / "processed" / "apis.jsonl"
+OUT = HERE / "out"
+LEVELS = {"n50": OUT / "trajectories_all_v6_n50.jsonl",
+          "n20": OUT / "trajectories_all_v6_n20.jsonl"}
+
+
+def seqs_from(path: Path):
+    out = []
+    for line in path.read_text(encoding="utf-8").splitlines():
+        if not line.strip():
+            continue
+        s = [c["name"] for c in json.loads(line).get("calls", []) if c.get("name")]
+        if s:
+            out.append(s)
+    return out
+
+
+def build(seqs):
+    t = Trie()
+    for s in seqs:
+        t.insert(list(s))
+    return t
+
+
+def stats(trie, classify):
+    lines, st, _ = _text_tree(trie.root, classify, 1)
+    depths = []
+
+    def walk(node, d):
+        if not node.children:
+            depths.append(d); return
+        for c in node.children.values():
+            walk(c, d + 1)
+    walk(trie.root, 0)
+    return dict(nodes=st["nodes"], max_depth=st["max_depth"],
+               root_branch=len(trie.root.children), leaves=len(depths),
+               mean_leaf_depth=sum(depths) / max(len(depths), 1)), lines
+
+
+def main():
+    try:
+        sys.stdout.reconfigure(encoding="utf-8", errors="replace")
+    except Exception:
+        pass
+    real_names = _load_names(REAL_APIS)
+    conf_names = _load_names(N100 / "apis.jsonl")
+
+    def classify(name: str) -> str:
+        if name in conf_names:
+            return "confuser"
+        if name in real_names:
+            return "real"
+        return "?"
+
+    for level, path in LEVELS.items():
+        seqs = seqs_from(path)
+        trie = build(seqs)
+        st, lines = stats(trie, classify)
+        stem = HERE / f"trie_v6_{level}"
+        header = [
+            f"v6 UNBUNDLED CONFUSER TRIE ({level})  — subset of the finalized v6 dataset",
+            "=" * 72,
+            f"rows: {len(seqs)}   nodes: {st['nodes']}   max depth: {st['max_depth']}   "
+            f"root branches: {st['root_branch']}   mean leaf depth: {st['mean_leaf_depth']:.2f}",
+            "Legend: [real] BLUE = real prefix the confuser anchors to;  "
+            "[confuser] ORANGE = retail look-alike (the divergence node F).",
+            "=" * 72, "",
+        ]
+        stem.with_suffix(".txt").write_text("\n".join(header + lines), encoding="utf-8")
+        png = _render_image(trie.root, classify, stem, 1, "png")
+        svg = _render_image(trie.root, classify, stem, 1, "svg")
+        print(f"{level}: rows={len(seqs)} nodes={st['nodes']} max_depth={st['max_depth']} "
+              f"root_branch={st['root_branch']} mean_leaf_depth={st['mean_leaf_depth']:.2f}")
+        print(f"   txt -> {stem.with_suffix('.txt').name}   png -> {png}   svg -> {svg}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tempscripts/story_remediation/validate_literals.py b/tempscripts/story_remediation/validate_literals.py
new file mode 100644
index 0000000000000000000000000000000000000000..53c4ee10d5ada149733c85028712cea386326c23
--- /dev/null
+++ b/tempscripts/story_remediation/validate_literals.py
@@ -0,0 +1,54 @@
+"""Safety net: verify every DB literal in a caught row's ORIGINAL query still
+appears in PROPOSALS.md. Order #s / gift-card IDs / item numbers are unique per
+row, so whole-file presence effectively proves per-row preservation. Flags drops.
+
+Usage: python temp/story_remediation/validate_literals.py
+"""
+import json, re
+from pathlib import Path
+
+HERE = Path(__file__).resolve().parent
+OUT = HERE / "out"
+
+done = {l.strip() for l in (OUT / "done_ids.txt").read_text(encoding="utf-8").splitlines() if l.strip()}
+rows = {json.loads(l)["item_id"]: json.loads(l)
+        for l in (OUT / "caught_rows.jsonl").read_text(encoding="utf-8").splitlines() if l.strip()}
+md = (HERE / "PROPOSALS.md").read_text(encoding="utf-8")
+
+PATS = {
+    "order": r"#W\d+",
+    "giftcard": r"gift_card_\d+",
+    "email": r"[\w.\-]+@[\w.\-]+",
+    "phone": r"\+1-\d{3}-\d{3}-\d{4}",
+    "itemnum": r"\b\d{7,}\b",
+    "quote": r"'[^']{3,}'",
+    "money": r"\$\d+",
+    "zip": r"\b\d{5}\b",
+    "promo": r"\b[A-Z]{3,}\d{1,3}\b",
+}
+
+
+def literals(text):
+    out = set()
+    for _, p in PATS.items():
+        for m in re.findall(p, text):
+            out.add(m)
+    return out
+
+
+problems = 0
+checked = 0
+for iid in done:
+    r = rows.get(iid)
+    if not r:
+        continue
+    checked += 1
+    src = r["query"] + " " + " ".join(h["content"] for h in r["history"])
+    for lit in literals(r["query"]):
+        # ignore bare 5-digit ZIPs that are substrings of order numbers etc.
+        if lit not in md:
+            print(f"MISSING literal {lit!r} for {iid}")
+            problems += 1
+
+print(f"\nchecked {checked} done rows | missing literals: {problems}")
+print("OK - all literals preserved" if problems == 0 else "REVIEW NEEDED")