src/tests/test_ctx_init.py

"""Tests for ctx_init — bootstrap ~/.claude/ scaffolding."""

from __future__ import annotations

import builtins
import hashlib
import io
import json
import sqlite3
import sys
import tarfile
import zlib
from pathlib import Path
from types import SimpleNamespace

import networkx as nx
import pytest
import ctx_init as ci
from ctx.core.graph.graph_packs import write_base_pack
from ctx.core.graph.graph_store import validate_graph_store
from ctx.core.wiki.wiki_packs import write_wiki_base_pack


def _write_dashboard_index(path: Path, *, export_id: str = "test-export") -> None:
    conn = sqlite3.connect(path)
    try:
        conn.execute("CREATE TABLE meta(key TEXT PRIMARY KEY, value TEXT NOT NULL)")
        conn.execute(
            "CREATE TABLE nodes(id TEXT PRIMARY KEY,label TEXT,type TEXT,tags TEXT,"
            "description TEXT,quality_score REAL,usage_score REAL,degree INTEGER)"
        )
        conn.execute(
            "CREATE TABLE slug_index(slug TEXT,type TEXT,node_id TEXT,"
            "PRIMARY KEY(slug,type,node_id))"
        )
        conn.execute("CREATE TABLE neighbors(source TEXT PRIMARY KEY, payload BLOB NOT NULL)")
        conn.executemany(
            "INSERT INTO meta VALUES(?,?)",
            [
                ("export_id", json.dumps(export_id)),
                ("nodes_count", "1"),
                ("edges_count", "0"),
                ("max_degree", "1"),
                ("top_k", "40"),
            ],
        )
        conn.execute(
            "INSERT INTO nodes VALUES(?,?,?,?,?,?,?,?)",
            ("skill:current", "current", "skill", "[]", "", None, None, 0),
        )
        conn.execute("INSERT INTO slug_index VALUES(?,?,?)", ("current", "skill", "skill:current"))
        conn.execute("INSERT INTO neighbors VALUES(?,?)", ("skill:current", zlib.compress(b"[]")))
        conn.commit()
    finally:
        conn.close()


def _artifact_sha256_or_lfs_oid(path: Path, *, normalize_text: bool = False) -> str:
    data = path.read_bytes()
    if data.startswith(b"version https://git-lfs.github.com/spec/v1\n"):
        for line in data.decode("utf-8").splitlines():
            if line.startswith("oid sha256:"):
                return line.removeprefix("oid sha256:")
    if normalize_text:
        data = data.replace(b"\r\n", b"\n")
    return hashlib.sha256(data).hexdigest()


def test_ensure_directories_creates_standard_tree(tmp_path: Path) -> None:
    created = ci.ensure_directories(tmp_path)
    # First call should create every standard subdir.
    assert len(created) == len(ci._STANDARD_SUBDIRS)
    for sub in ci._STANDARD_SUBDIRS:
        assert (tmp_path / sub).is_dir(), f"missing {sub}"


def test_ensure_directories_is_idempotent(tmp_path: Path) -> None:
    first = ci.ensure_directories(tmp_path)
    assert len(first) > 0
    second = ci.ensure_directories(tmp_path)
    assert second == [], "second call should not recreate anything"


def test_seed_user_config_writes_once(tmp_path: Path) -> None:
    tmp_path.mkdir(exist_ok=True)
    first = ci.seed_user_config(tmp_path)
    assert first is not None
    assert first.exists()
    body = first.read_text(encoding="utf-8")
    assert "skill-system-config.json" in body

    # Second call returns None (file already exists, force=False).
    second = ci.seed_user_config(tmp_path)
    assert second is None


def test_seed_user_config_respects_force(tmp_path: Path) -> None:
    target = tmp_path / "skill-system-config.json"
    target.write_text("user-custom-content", encoding="utf-8")
    # Without force → don't touch.
    assert ci.seed_user_config(tmp_path, force=False) is None
    assert target.read_text() == "user-custom-content"
    # With force → overwrite.
    result = ci.seed_user_config(tmp_path, force=True)
    assert result == target
    assert "skill-system-config.json" in target.read_text()


def test_main_creates_everything_in_dry_mode(tmp_path: Path, monkeypatch,
                                              capsys) -> None:
    """End-to-end: ``ctx-init`` (no flags) creates dirs + config + toolboxes
    without touching hooks or graph."""
    monkeypatch.setattr(ci, "_claude_dir", lambda: tmp_path)

    # Short-circuit subprocess.run to avoid spawning a real toolbox/graph CLI
    # in tests. Verify that main() doesn't call install_hooks or build_graph
    # when those flags are absent.
    calls: list[list[str]] = []

    class _FakeResult:
        returncode = 0
        stdout = ""
        stderr = ""

    def fake_run(cmd, **kwargs):
        calls.append(list(cmd))
        return _FakeResult()

    monkeypatch.setattr(ci.subprocess, "run", fake_run)

    rc = ci.main([])
    assert rc == 0
    # toolbox init should have been invoked
    toolbox_calls = [c for c in calls if "toolbox" in " ".join(c)]
    assert toolbox_calls, "toolbox init not invoked"
    # inject_hooks / wiki_graphify must NOT be invoked without flags
    for c in calls:
        assert "inject_hooks" not in " ".join(c)
        assert "wiki_graphify" not in " ".join(c)

    out = capsys.readouterr().out
    assert "[ok]" in out
    assert "[skip] hook injection" in out
    assert "[skip] graph install" in out


def test_main_treats_existing_toolboxes_as_idempotent_skip(
    tmp_path: Path,
    monkeypatch,
    capsys,
) -> None:
    monkeypatch.setattr(ci, "_claude_dir", lambda: tmp_path)

    class _FakeResult:
        returncode = 1
        stdout = ""
        stderr = (
            "Global config already has 5 toolbox(es). "
            "Use --force to overwrite."
        )

    monkeypatch.setattr(ci.subprocess, "run", lambda *_args, **_kwargs: _FakeResult())

    rc = ci.main(["--model-mode", "skip"])
    captured = capsys.readouterr()

    assert rc == 0
    assert "starter toolboxes already present" in captured.out
    assert "toolbox init returned" not in captured.err
    assert "Global config already has" not in captured.err


def test_main_auto_wizard_in_terminal_configures_custom_model(
    tmp_path: Path,
    monkeypatch,
) -> None:
    monkeypatch.setattr(ci, "_claude_dir", lambda: tmp_path)
    monkeypatch.setattr(ci, "_stdio_is_interactive", lambda: True)
    monkeypatch.setattr(
        ci,
        "recommend_harnesses",
        lambda goal, top_k=5, model_provider=None, model=None: [],
    )

    answers = iter([
        "y",                  # hooks
        "enriched",           # knowledge mode
        "n",                  # graph
        "custom",             # model mode
        "openai/gpt-5.5",     # model
        "",                   # provider default: openai
        "",                   # api key env default: OPENAI_API_KEY
        "",                   # base URL
        "build CAD artifacts",
        "windows python",      # runtime / OS
        "supervised",          # autonomy
        "filesystem shell",    # allowed tools
        "pytest ruff",         # verification
        "private repo",        # privacy / network
        "mcp",                 # attach mode
        "n",                  # validate model
    ])
    monkeypatch.setattr(builtins, "input", lambda _prompt: next(answers))
    calls: list[list[str]] = []

    class _FakeResult:
        returncode = 0
        stdout = ""
        stderr = ""

    def _fake_run(cmd: list[str], **_kwargs: object) -> _FakeResult:
        calls.append(list(cmd))
        return _FakeResult()

    monkeypatch.setattr(ci.subprocess, "run", _fake_run)

    rc = ci.main([])

    assert rc == 0
    assert any("ctx.adapters.claude_code.inject_hooks" in c for c in calls)
    assert not any("ctx.core.wiki.wiki_graphify" in c for c in calls)
    profile = json.loads((tmp_path / "ctx-model-profile.json").read_text())
    assert profile["mode"] == "custom"
    assert profile["provider"] == "openai"
    assert profile["model"] == "openai/gpt-5.5"
    assert profile["api_key_env"] == "OPENAI_API_KEY"
    assert profile["goal"] == "build CAD artifacts"
    assert profile["knowledge_mode"] == "enriched"
    assert profile["harness_requirements"] == {
        "runtime": "windows python",
        "autonomy": "supervised",
        "tools": "filesystem shell",
        "verification": "pytest ruff",
        "privacy": "private repo",
        "attach_mode": "mcp",
        "api_key_env": "OPENAI_API_KEY",
    }
    user_config = json.loads((tmp_path / "skill-system-config.json").read_text())
    assert user_config["knowledge"]["mode"] == "enriched"


def test_wizard_flag_prompts_without_tty(tmp_path: Path, monkeypatch) -> None:
    monkeypatch.setattr(ci, "_claude_dir", lambda: tmp_path)
    monkeypatch.setattr(ci, "_stdio_is_interactive", lambda: False)
    monkeypatch.setattr(ci, "seed_toolboxes", lambda force=False: 0)
    monkeypatch.setattr(
        ci,
        "recommend_harnesses",
        lambda goal, top_k=5, model_provider=None, model=None: [],
    )

    answers = iter([
        "n",                  # hooks
        "local",              # knowledge mode
        "claude-code",        # model mode
        "maintain FastAPI services",
    ])
    monkeypatch.setattr(builtins, "input", lambda _prompt: next(answers))

    rc = ci.main(["--wizard"])

    assert rc == 0
    profile = json.loads((tmp_path / "ctx-model-profile.json").read_text())
    assert profile["mode"] == "claude-code"
    assert profile["goal"] == "maintain FastAPI services"
    assert profile["knowledge_mode"] == "local"
    user_config = json.loads((tmp_path / "skill-system-config.json").read_text())
    assert user_config["knowledge"]["mode"] == "local"


def test_explicit_args_do_not_auto_wizard_in_terminal(
    tmp_path: Path,
    monkeypatch,
) -> None:
    monkeypatch.setattr(ci, "_claude_dir", lambda: tmp_path)
    monkeypatch.setattr(ci, "_stdio_is_interactive", lambda: True)
    monkeypatch.setattr(ci, "seed_toolboxes", lambda force=False: 0)
    monkeypatch.setattr(
        builtins,
        "input",
        lambda _prompt: (_ for _ in ()).throw(AssertionError("unexpected prompt")),
    )

    assert ci.main(["--model-mode", "skip", "--knowledge-mode", "local"]) == 0
    user_config = json.loads((tmp_path / "skill-system-config.json").read_text())
    assert user_config["knowledge"]["mode"] == "local"


def test_main_with_hooks_flag_invokes_inject(tmp_path: Path, monkeypatch) -> None:
    monkeypatch.setattr(ci, "_claude_dir", lambda: tmp_path)
    calls: list[list[str]] = []

    class _FakeResult:
        returncode = 0
        stdout = ""
        stderr = ""

    def _fake_run(cmd: list[str], **_kwargs: object) -> _FakeResult:
        calls.append(list(cmd))
        return _FakeResult()

    monkeypatch.setattr(ci.subprocess, "run", _fake_run)
    rc = ci.main(["--hooks"])
    assert rc == 0
    assert any("ctx.adapters.claude_code.inject_hooks" in c for c in calls)
    assert not any(c == "inject_hooks" for call in calls for c in call)


def _write_graph_archive(
    tmp_path: Path,
    *,
    include_graph_pack: bool = False,
    graph_pack_export_id: str = "test-export",
    include_wiki_pack: bool = False,
    wiki_pack_export_id: str = "test-export",
) -> Path:
    source = tmp_path / "archive-source"
    graph_out = source / "graphify-out"
    graph_out.mkdir(parents=True)
    (graph_out / "graph.json").write_text(
        json.dumps({"graph": {"export_id": "test-export"}, "nodes": [], "links": []}),
        encoding="utf-8",
    )
    (graph_out / "graph-delta.json").write_text(
        json.dumps({"export_id": "test-export", "nodes": [], "edges": []}),
        encoding="utf-8",
    )
    (graph_out / "communities.json").write_text(
        json.dumps({"export_id": "test-export", "total_communities": 0}),
        encoding="utf-8",
    )
    (graph_out / "graph-report.md").write_text(
        "# Graph Report\n\n> Export ID: test-export\n",
        encoding="utf-8",
    )
    (graph_out / "graph-export-manifest.json").write_text(
        json.dumps({
            "version": 1,
            "export_id": "test-export",
            "artifacts": {
                "graph": "graph.json",
                "delta": "graph-delta.json",
                "communities": "communities.json",
                "report": "graph-report.md",
            },
        }),
        encoding="utf-8",
    )
    _write_dashboard_index(graph_out / "dashboard-neighborhoods.sqlite3")
    external = source / "external-catalogs" / "skills-sh"
    external.mkdir(parents=True)
    (external / "catalog.json").write_text("{}", encoding="utf-8")
    entities = source / "entities" / "skills"
    entities.mkdir(parents=True)
    (entities / "current.md").write_text("# Current\n", encoding="utf-8")
    (source / "index.md").write_text("# Wiki\n", encoding="utf-8")
    if include_graph_pack:
        graph = nx.Graph()
        graph.add_node("skill:current", label="current", type="skill")
        write_base_pack(
            pack_dir=graph_out / "packs" / f"base-{graph_pack_export_id}",
            pack_id=f"base-{graph_pack_export_id}",
            base_export_id=graph_pack_export_id,
            config_hash="config-1",
            model_id="model-1",
            graph=graph,
        )
    if include_wiki_pack:
        write_wiki_base_pack(
            pack_dir=source / "wiki-packs" / f"base-{wiki_pack_export_id}",
            pack_id=f"base-{wiki_pack_export_id}",
            base_export_id=wiki_pack_export_id,
            pages={
                "index.md": "# Wiki\n",
                "entities/skills/current.md": "# Current\n",
            },
        )
    archive = tmp_path / "wiki-graph.tar.gz"
    with tarfile.open(archive, "w:gz") as tf:
        for path in sorted(source.rglob("*")):
            if path.is_file():
                tf.add(path, arcname=path.relative_to(source).as_posix())
    return archive


def _tar_text(tf: tarfile.TarFile, name: str, text: str) -> None:
    payload = text.encode("utf-8")
    info = tarfile.TarInfo(name)
    info.size = len(payload)
    tf.addfile(info, io.BytesIO(payload))


def _tar_bytes(tf: tarfile.TarFile, name: str, payload: bytes) -> None:
    info = tarfile.TarInfo(name)
    info.size = len(payload)
    tf.addfile(info, io.BytesIO(payload))


def test_download_graph_archive_verifies_sha256(
    tmp_path: Path,
    monkeypatch,
) -> None:
    payload = b"graph archive bytes"

    class _Response(io.BytesIO):
        def __enter__(self) -> "_Response":
            return self

        def __exit__(self, *_args: object) -> None:
            return None

    monkeypatch.setattr(
        ci.urllib.request,
        "urlopen",
        lambda _url, timeout=120: _Response(payload),
    )

    destination = tmp_path / "wiki-graph.tar.gz"
    ci._download_graph_archive(
        destination,
        url="https://example.invalid/wiki-graph.tar.gz",
        expected_sha256=hashlib.sha256(payload).hexdigest(),
    )
    assert destination.read_bytes() == payload

    bad_destination = tmp_path / "bad-wiki-graph.tar.gz"
    with pytest.raises(ValueError, match="checksum mismatch"):
        ci._download_graph_archive(
            bad_destination,
            url="https://example.invalid/wiki-graph.tar.gz",
            expected_sha256="0" * 64,
        )
    assert not bad_destination.exists()


def test_graph_download_checksums_match_shipped_artifacts() -> None:
    root = Path(__file__).resolve().parent.parent.parent
    for mode, archive_name in ci._GRAPH_ARCHIVE_NAMES.items():
        path = root / "graph" / archive_name
        assert ci._GRAPH_ARCHIVE_SHA256[mode] == _artifact_sha256_or_lfs_oid(path)

    overlay_path = root / "graph" / ci._GRAPH_ENTITY_OVERLAY_NAME
    assert ci._GRAPH_ENTITY_OVERLAY_SHA256 == _artifact_sha256_or_lfs_oid(
        overlay_path,
        normalize_text=True,
    )


def test_local_graph_archive_checksum_is_verified(tmp_path: Path) -> None:
    archive = tmp_path / "wiki-graph-runtime.tar.gz"
    archive.write_bytes(b"not the shipped runtime archive")

    with pytest.raises(ValueError, match="local graph archive checksum mismatch"):
        ci._verify_local_graph_archive(archive, requested_install_mode="runtime")


def test_lfs_pointer_graph_archive_is_ignored(
    tmp_path: Path,
    monkeypatch: pytest.MonkeyPatch,
) -> None:
    graph_dir = tmp_path / "graph"
    graph_dir.mkdir()
    (graph_dir / "wiki-graph-runtime.tar.gz").write_text(
        "version https://git-lfs.github.com/spec/v1\n"
        "oid sha256:993fc08377fdb09edcff4414c59b10fc121189b4a161bf796e3f8f6600907bb1\n"
        "size 122141091\n",
        encoding="utf-8",
    )
    cwd = tmp_path / "cwd"
    cwd.mkdir()
    monkeypatch.chdir(cwd)
    monkeypatch.setattr(ci, "__file__", str(tmp_path / "src" / "ctx_init.py"))

    assert ci._find_local_graph_archive("runtime") is None


def test_custom_graph_url_requires_checksum_or_explicit_opt_out(
    tmp_path: Path,
    monkeypatch,
) -> None:
    monkeypatch.setattr(ci, "_find_local_graph_archive", lambda _mode: None)
    monkeypatch.setattr(
        ci,
        "_download_graph_archive",
        lambda *_args, **_kwargs: (_ for _ in ()).throw(
            AssertionError("download should be blocked before network access")
        ),
    )

    rc = ci.build_graph(
        tmp_path / "home",
        graph_url="https://example.invalid/wiki-graph.tar.gz",
    )

    assert rc == 1


def test_custom_graph_url_bypasses_local_archive(
    tmp_path: Path,
    monkeypatch,
) -> None:
    archive = _write_graph_archive(tmp_path)
    archive_bytes = archive.read_bytes()
    calls: list[dict[str, object]] = []

    monkeypatch.setattr(
        ci,
        "_find_local_graph_archive",
        lambda _mode: (_ for _ in ()).throw(
            AssertionError("explicit graph_url must not use local archive")
        ),
    )

    def fake_download(destination: Path, **kwargs: object) -> None:
        calls.append(dict(kwargs))
        destination.write_bytes(archive_bytes)

    monkeypatch.setattr(ci, "_download_graph_archive", fake_download)
    monkeypatch.setattr(ci, "_install_graph_entity_overlay", lambda *_a, **_k: None)

    rc = ci.build_graph(
        tmp_path / "home",
        graph_url="https://example.invalid/custom-wiki-graph.tar.gz",
        graph_sha256=hashlib.sha256(archive_bytes).hexdigest(),
    )

    assert rc == 0
    assert calls == [
        {
            "url": "https://example.invalid/custom-wiki-graph.tar.gz",
            "expected_sha256": hashlib.sha256(archive_bytes).hexdigest(),
        }
    ]


def test_main_with_graph_flag_installs_prebuilt_graph(
    tmp_path: Path,
    monkeypatch,
) -> None:
    claude = tmp_path / "home"
    archive = _write_graph_archive(tmp_path)
    monkeypatch.setattr(ci, "_claude_dir", lambda: claude)
    monkeypatch.setattr(ci, "seed_toolboxes", lambda force=False: 0)
    monkeypatch.setattr(
        ci,
        "_find_local_graph_archive",
        lambda _install_mode="runtime": archive,
        raising=False,
    )
    monkeypatch.setattr(ci, "_verify_local_graph_archive", lambda *_a, **_k: None)
    monkeypatch.setattr(
        ci,
        "_download_graph_archive",
        lambda _dest, **_kwargs: (_ for _ in ()).throw(
            AssertionError("unexpected release download")
        ),
        raising=False,
    )
    calls: list[list[str]] = []

    class _FakeResult:
        returncode = 0
        stdout = ""
        stderr = ""

    def _fake_run(cmd: list[str], **_kwargs: object) -> _FakeResult:
        calls.append(list(cmd))
        return _FakeResult()

    monkeypatch.setattr(ci.subprocess, "run", _fake_run)
    rc = ci.main(["--graph", "--model-mode", "skip"])
    assert rc == 0
    graph_json = claude / "skill-wiki" / "graphify-out" / "graph.json"
    graph_payload = json.loads(graph_json.read_text(encoding="utf-8"))
    assert graph_payload["graph"]["export_id"] == "test-export"
    assert not (
        claude / "skill-wiki" / "entities" / "skills" / "current.md"
    ).exists()
    assert not any("ctx.core.wiki.wiki_graphify" in c for c in calls)
    assert not any(c == "wiki_graphify" for call in calls for c in call)


def test_graph_install_copies_local_entity_overlay(
    tmp_path: Path,
    monkeypatch,
) -> None:
    claude = tmp_path / "home"
    archive = _write_graph_archive(tmp_path)
    overlay = tmp_path / "entity-overlays.jsonl"
    overlay.write_text(
        json.dumps({
            "overlay_id": "test-overlay",
            "nodes": [{"id": "harness:mirage", "type": "harness"}],
            "edges": [
                {
                    "source": "harness:mirage",
                    "target": "skill:codex-review",
                    "weight": 0.5,
                    "similarity_score": 0.5,
                    "method": "manual_direct_overlay_v1",
                    "rank": 1,
                    "provenance": "manual_overlay_v1",
                }
            ],
        })
        + "\n",
        encoding="utf-8",
    )
    monkeypatch.setattr(
        ci,
        "_find_local_graph_archive",
        lambda _install_mode="runtime": archive,
        raising=False,
    )
    monkeypatch.setattr(ci, "_find_local_graph_entity_overlay", lambda: overlay)
    monkeypatch.setattr(ci, "_verify_local_graph_archive", lambda *_a, **_k: None)

    assert ci.build_graph(claude) == 0

    installed = claude / "skill-wiki" / "graphify-out" / "entity-overlays.jsonl"
    payload = json.loads(installed.read_text(encoding="utf-8"))
    assert payload["overlay_id"] == "test-overlay"
    assert payload["edges"][0]["method"] == "manual_direct_overlay_v1"


@pytest.mark.parametrize("field", ["semantic_sim", "tag_sim", "token_sim"])
def test_graph_overlay_validation_rejects_out_of_range_similarity_fields(
    tmp_path: Path,
    field: str,
) -> None:
    overlay = tmp_path / "entity-overlays.jsonl"
    overlay.write_text(
        json.dumps({
            "nodes": [{"id": "skill:a"}],
            "edges": [
                {
                    "source": "skill:a",
                    "target": "skill:b",
                    "weight": 0.5,
                    "final_weight": 0.5,
                    field: 2.0,
                },
            ],
        })
        + "\n",
        encoding="utf-8",
    )

    with pytest.raises(ValueError, match=f"{field} must be 0..1"):
        ci._validate_graph_entity_overlay(overlay)


def test_graph_overlay_validation_rejects_weight_final_weight_drift(
    tmp_path: Path,
) -> None:
    overlay = tmp_path / "entity-overlays.jsonl"
    overlay.write_text(
        json.dumps({
            "nodes": [{"id": "skill:a"}],
            "edges": [
                {
                    "source": "skill:a",
                    "target": "skill:b",
                    "weight": 0.7,
                    "final_weight": 0.5,
                },
            ],
        })
        + "\n",
        encoding="utf-8",
    )

    with pytest.raises(ValueError, match="weight must equal final_weight"):
        ci._validate_graph_entity_overlay(overlay)


def test_runtime_graph_install_extracts_harness_pages_after_required_files(
    tmp_path: Path,
    monkeypatch,
) -> None:
    archive = tmp_path / "ordered-runtime-wiki-graph.tar.gz"
    with tarfile.open(archive, "w:gz") as tf:
        _tar_text(
            tf,
            "graphify-out/graph.json",
            json.dumps({
                "graph": {"export_id": "test-export"},
                "nodes": [{"id": "harness:text-to-cad", "type": "harness"}],
                "links": [],
            }),
        )
        _tar_text(
            tf,
            "graphify-out/graph-delta.json",
            json.dumps({"export_id": "test-export", "nodes": [], "edges": []}),
        )
        _tar_text(
            tf,
            "graphify-out/communities.json",
            json.dumps({"export_id": "test-export", "total_communities": 0}),
        )
        _tar_text(tf, "graphify-out/graph-report.md", "# Graph Report\n")
        _tar_text(
            tf,
            "graphify-out/graph-export-manifest.json",
            json.dumps({
                "version": 1,
                "export_id": "test-export",
                "artifacts": {
                    "graph": "graph.json",
                    "delta": "graph-delta.json",
                    "communities": "communities.json",
                    "report": "graph-report.md",
                },
            }),
        )
        index_path = tmp_path / "runtime-dashboard-neighborhoods.sqlite3"
        _write_dashboard_index(index_path)
        _tar_bytes(
            tf,
            "graphify-out/dashboard-neighborhoods.sqlite3",
            index_path.read_bytes(),
        )
        _tar_text(tf, "external-catalogs/skills-sh/catalog.json", "{}")
        _tar_text(tf, "index.md", "# Wiki\n")
        _tar_text(tf, "entities/harnesses/text-to-cad.md", "# Text to CAD\n")
        _tar_text(tf, "entities/skills/not-runtime.md", "# Not runtime\n")

    claude = tmp_path / "home"
    monkeypatch.setattr(
        ci,
        "_find_local_graph_archive",
        lambda _install_mode="runtime": archive,
    )
    monkeypatch.setattr(ci, "_verify_local_graph_archive", lambda *_a, **_k: None)

    assert ci.build_graph(claude) == 0
    assert (
        claude / "skill-wiki" / "entities" / "harnesses" / "text-to-cad.md"
    ).is_file()
    assert not (
        claude / "skill-wiki" / "entities" / "skills" / "not-runtime.md"
    ).exists()


def test_runtime_graph_install_preserves_existing_non_harness_entities(
    tmp_path: Path,
    monkeypatch,
) -> None:
    archive = _write_graph_archive(tmp_path)
    claude = tmp_path / "home"
    local_skill = claude / "skill-wiki" / "entities" / "skills" / "private.md"
    local_agent = claude / "skill-wiki" / "entities" / "agents" / "private.md"
    local_mcp = claude / "skill-wiki" / "entities" / "mcp-servers" / "p" / "private.md"
    local_harness = claude / "skill-wiki" / "entities" / "harnesses" / "old.md"
    for path in (local_skill, local_agent, local_mcp, local_harness):
        path.parent.mkdir(parents=True, exist_ok=True)
        path.write_text(f"# {path.stem}\n", encoding="utf-8")

    monkeypatch.setattr(
        ci,
        "_find_local_graph_archive",
        lambda _install_mode="runtime": archive,
    )
    monkeypatch.setattr(ci, "_verify_local_graph_archive", lambda *_a, **_k: None)
    monkeypatch.setattr(ci, "_install_graph_entity_overlay", lambda *_a, **_k: None)

    assert ci.build_graph(claude, force=True, install_mode="runtime") == 0

    assert local_skill.is_file()
    assert local_agent.is_file()
    assert local_mcp.is_file()
    assert not local_harness.exists()


def test_graph_install_rejects_incomplete_archive(
    tmp_path: Path,
    monkeypatch,
) -> None:
    source = tmp_path / "incomplete-source"
    graph_out = source / "graphify-out"
    graph_out.mkdir(parents=True)
    (graph_out / "graph.json").write_text(
        json.dumps({"graph": {"export_id": "partial"}, "nodes": []}),
        encoding="utf-8",
    )
    archive = tmp_path / "incomplete-wiki-graph.tar.gz"
    with tarfile.open(archive, "w:gz") as tf:
        tf.add(graph_out / "graph.json", arcname="graphify-out/graph.json")

    claude = tmp_path / "home"
    monkeypatch.setattr(
        ci,
        "_find_local_graph_archive",
        lambda _install_mode="runtime": archive,
    )
    monkeypatch.setattr(ci, "_verify_local_graph_archive", lambda *_a, **_k: None)

    assert ci.build_graph(claude) == 1
    assert not (claude / "skill-wiki" / "graphify-out" / "graph.json").exists()


def test_graph_install_validation_does_not_parse_full_graph_json(
    tmp_path: Path,
    monkeypatch,
) -> None:
    wiki = tmp_path / "wiki"
    graph_out = wiki / "graphify-out"
    graph_out.mkdir(parents=True)
    (wiki / "index.md").write_text("# Wiki\n", encoding="utf-8")
    (graph_out / "graph.json").write_text(
        json.dumps({"graph": {"export_id": "test-export"}, "nodes": [], "links": []}),
        encoding="utf-8",
    )
    (graph_out / "graph-delta.json").write_text(
        json.dumps({"export_id": "test-export", "nodes": [], "edges": []}),
        encoding="utf-8",
    )
    (graph_out / "communities.json").write_text(
        json.dumps({"export_id": "test-export", "total_communities": 0}),
        encoding="utf-8",
    )
    (graph_out / "graph-report.md").write_text(
        "# Graph Report\n\n> Export ID: test-export\n",
        encoding="utf-8",
    )
    (graph_out / "graph-export-manifest.json").write_text(
        json.dumps({
            "version": 1,
            "export_id": "test-export",
            "artifacts": {
                "graph": "graph.json",
                "delta": "graph-delta.json",
                "communities": "communities.json",
                "report": "graph-report.md",
            },
        }),
        encoding="utf-8",
    )
    _write_dashboard_index(graph_out / "dashboard-neighborhoods.sqlite3")
    external = wiki / "external-catalogs" / "skills-sh"
    external.mkdir(parents=True)
    (external / "catalog.json").write_text("{}", encoding="utf-8")

    def guarded_read(path: Path) -> object:
        if path.name == "graph.json":
            raise AssertionError("install validation must not parse full graph.json")
        return json.loads(path.read_text(encoding="utf-8"))

    monkeypatch.setattr(ci, "_read_json_file", guarded_read)

    ci._validate_graph_install_tree(wiki)


def test_graph_json_outline_scans_middle_for_edges_key(
    tmp_path: Path,
    monkeypatch: pytest.MonkeyPatch,
) -> None:
    monkeypatch.setattr(ci, "_GRAPH_JSON_OUTLINE_BYTES", 32)
    filler = "x" * 256
    graph_json = tmp_path / "graph.json"
    graph_json.write_text(
        '{"nodes":["' + filler + '"],"edges":[],"graph":"' + filler + '"}',
        encoding="utf-8",
    )

    ci._validate_graph_json_outline(graph_json)


def test_graph_install_validation_accepts_base_pack_without_graph_json(
    tmp_path: Path,
) -> None:
    wiki = tmp_path / "wiki"
    graph_out = wiki / "graphify-out"
    graph_out.mkdir(parents=True)
    (wiki / "index.md").write_text("# Wiki\n", encoding="utf-8")
    graph = nx.Graph()
    graph.add_node("skill:pack-only", label="pack-only", type="skill")
    write_base_pack(
        pack_dir=graph_out / "packs" / "base-export-1",
        pack_id="base-export-1",
        base_export_id="test-export",
        config_hash="config-1",
        model_id="model-1",
        graph=graph,
    )
    (graph_out / "graph-delta.json").write_text(
        json.dumps({"export_id": "test-export", "nodes": [], "edges": []}),
        encoding="utf-8",
    )
    (graph_out / "communities.json").write_text(
        json.dumps({"export_id": "test-export", "total_communities": 0}),
        encoding="utf-8",
    )
    (graph_out / "graph-report.md").write_text(
        "# Graph Report\n\n> Export ID: test-export\n",
        encoding="utf-8",
    )
    (graph_out / "graph-export-manifest.json").write_text(
        json.dumps({
            "version": 1,
            "export_id": "test-export",
            "artifacts": {
                "graph": "graph.json",
                "delta": "graph-delta.json",
                "communities": "communities.json",
                "report": "graph-report.md",
            },
        }),
        encoding="utf-8",
    )
    _write_dashboard_index(graph_out / "dashboard-neighborhoods.sqlite3")
    external = wiki / "external-catalogs" / "skills-sh"
    external.mkdir(parents=True)
    (external / "catalog.json").write_text("{}", encoding="utf-8")

    ci._validate_graph_install_tree(wiki)


def test_runtime_graph_install_extracts_and_validates_wiki_packs(
    tmp_path: Path,
) -> None:
    archive = _write_graph_archive(tmp_path, include_wiki_pack=True)
    wiki = tmp_path / "installed-wiki"

    ci._extract_graph_archive(archive, wiki, install_mode="runtime")

    assert (wiki / "wiki-packs" / "base-test-export" / "wiki-pack-manifest.json").is_file()
    assert not (wiki / "entities" / "skills" / "current.md").exists()
    ci._validate_graph_install_tree(wiki)
    assert ci._graph_full_install_complete(wiki) is True


def test_runtime_graph_install_extracts_and_validates_graph_packs(
    tmp_path: Path,
) -> None:
    archive = _write_graph_archive(tmp_path, include_graph_pack=True)
    wiki = tmp_path / "installed-wiki"

    ci._extract_graph_archive(archive, wiki, install_mode="runtime")

    assert (
        wiki / "graphify-out" / "packs" / "base-test-export" / "graph-pack-manifest.json"
    ).is_file()
    ci._validate_graph_install_tree(wiki)


def test_build_graph_refreshes_operational_graph_store(
    tmp_path: Path,
    monkeypatch: pytest.MonkeyPatch,
) -> None:
    archive = _write_graph_archive(tmp_path, include_graph_pack=True)
    claude = tmp_path / "home"
    monkeypatch.setattr(
        ci,
        "_find_local_graph_archive",
        lambda _install_mode="runtime": archive,
    )
    monkeypatch.setattr(ci, "_verify_local_graph_archive", lambda *_a, **_k: None)
    monkeypatch.setattr(ci, "_install_graph_entity_overlay", lambda *_a, **_k: None)

    assert ci.build_graph(claude) == 0
    graph_dir = claude / "skill-wiki" / "graphify-out"
    store = graph_dir / "graph-store.sqlite3"
    assert validate_graph_store(store, graph_dir)["ok"] is True

    store.unlink()
    assert ci.build_graph(claude) == 0
    assert validate_graph_store(store, graph_dir)["ok"] is True


def test_graph_install_rejects_mismatched_graph_pack_export_id(
    tmp_path: Path,
) -> None:
    archive = _write_graph_archive(
        tmp_path,
        include_graph_pack=True,
        graph_pack_export_id="wrong-export",
    )

    with pytest.raises(ValueError, match="graphify-out/packs export_id mismatch"):
        ci._extract_graph_archive(archive, tmp_path / "installed-wiki", install_mode="runtime")


def test_graph_install_rejects_mismatched_wiki_pack_export_id(
    tmp_path: Path,
) -> None:
    archive = _write_graph_archive(
        tmp_path,
        include_wiki_pack=True,
        wiki_pack_export_id="wrong-export",
    )

    with pytest.raises(ValueError, match="wiki-packs export_id mismatch"):
        ci._extract_graph_archive(archive, tmp_path / "installed-wiki", install_mode="runtime")


def test_runtime_graph_install_without_full_entities_is_not_full_install(
    tmp_path: Path,
) -> None:
    archive = _write_graph_archive(tmp_path)
    wiki = tmp_path / "installed-wiki"

    ci._extract_graph_archive(archive, wiki, install_mode="runtime")

    assert ci._graph_install_complete(wiki) is True
    assert ci._graph_full_install_complete(wiki) is False


def test_full_graph_install_uses_system_tar_after_validation(
    tmp_path: Path,
    monkeypatch,
) -> None:
    archive = _write_graph_archive(tmp_path)
    wiki = tmp_path / "installed-wiki"
    calls: list[list[str]] = []

    def fake_run(cmd: list[str], **_kwargs: object) -> SimpleNamespace:
        calls.append(list(cmd))
        target = Path(cmd[cmd.index("-C") + 1])
        with tarfile.open(archive, "r:gz") as tf:
            tf.extractall(target)
        return SimpleNamespace(returncode=0, stdout="", stderr="")

    monkeypatch.setattr(ci.shutil, "which", lambda _name: "tar")
    monkeypatch.setattr(ci.subprocess, "run", fake_run)

    ci._extract_graph_archive(archive, wiki, install_mode="full")

    assert len(calls) == 1
    assert calls[0][:3] == ["tar", "-xzf", str(archive)]
    assert calls[0][3] == "-C"
    assert Path(calls[0][4]).name.startswith(".installed-wiki-stage-")
    assert ci._graph_full_install_complete(wiki) is True
    assert (wiki / "entities" / "skills" / "current.md").is_file()


def test_full_graph_install_prefers_wiki_packs_over_expanded_entities(
    tmp_path: Path,
    monkeypatch,
) -> None:
    archive = _write_graph_archive(tmp_path, include_wiki_pack=True)
    wiki = tmp_path / "installed-wiki"

    def fail_if_system_tar_is_used(*_args: object, **_kwargs: object) -> SimpleNamespace:
        pytest.fail("packed full install should use filtered extraction")

    monkeypatch.setattr(ci.shutil, "which", lambda _name: "tar")
    monkeypatch.setattr(ci.subprocess, "run", fail_if_system_tar_is_used)

    ci._extract_graph_archive(archive, wiki, install_mode="full")

    assert (wiki / "wiki-packs" / "base-test-export" / "wiki-pack-manifest.json").is_file()
    assert not (wiki / "entities" / "skills" / "current.md").exists()
    assert ci._graph_full_install_complete(wiki) is True


def test_graph_install_force_prunes_stale_generated_files(
    tmp_path: Path,
    monkeypatch,
    capsys,
) -> None:
    archive = _write_graph_archive(tmp_path)
    claude = tmp_path / "home"
    stale = claude / "skill-wiki" / "entities" / "skills" / "stale.md"
    stale.parent.mkdir(parents=True)
    stale.write_text("# Stale\n", encoding="utf-8")
    monkeypatch.setattr(ci, "_claude_dir", lambda: claude)
    monkeypatch.setattr(ci, "seed_toolboxes", lambda force=False: 0)
    monkeypatch.setattr(
        ci,
        "_find_local_graph_archive",
        lambda _install_mode="runtime": archive,
    )
    monkeypatch.setattr(ci, "_verify_local_graph_archive", lambda *_a, **_k: None)

    assert ci.main([
        "--graph",
        "--graph-install-mode", "full",
        "--force",
        "--model-mode", "skip",
    ]) == 0
    out = capsys.readouterr().out
    assert "full graph install expands the markdown LLM-wiki" in out
    assert "runtime mode is enough for recommendations" in out
    assert not stale.exists()
    assert (claude / "skill-wiki" / "entities" / "skills" / "current.md").is_file()


def test_graph_install_rejects_path_traversal_archive(
    tmp_path: Path,
    monkeypatch,
) -> None:
    archive = tmp_path / "malicious-wiki-graph.tar.gz"
    payload = b"owned"
    with tarfile.open(archive, "w:gz") as tf:
        info = tarfile.TarInfo("../evil.txt")
        info.size = len(payload)
        tf.addfile(info, io.BytesIO(payload))

    claude = tmp_path / "home"
    monkeypatch.setattr(
        ci,
        "_find_local_graph_archive",
        lambda _install_mode="runtime": archive,
    )
    monkeypatch.setattr(ci, "_verify_local_graph_archive", lambda *_a, **_k: None)

    assert ci.build_graph(claude) == 1
    assert not (tmp_path / "evil.txt").exists()
    assert not (claude / "evil.txt").exists()


def test_main_with_requested_hook_failure_exits_nonzero(
    tmp_path: Path, monkeypatch
) -> None:
    monkeypatch.setattr(ci, "_claude_dir", lambda: tmp_path)

    class _FakeResult:
        def __init__(self, returncode: int) -> None:
            self.returncode = returncode
            self.stdout = ""
            self.stderr = ""

    def fake_run(cmd, **kwargs):
        if "ctx.adapters.claude_code.inject_hooks" in cmd:
            return _FakeResult(7)
        return _FakeResult(0)

    monkeypatch.setattr(ci.subprocess, "run", fake_run)

    assert ci.main(["--hooks"]) == 7


def test_main_custom_model_writes_profile_and_recommends_harness(
    tmp_path: Path,
    monkeypatch,
    capsys,
) -> None:
    monkeypatch.setattr(ci, "_claude_dir", lambda: tmp_path)
    monkeypatch.setattr(ci, "seed_toolboxes", lambda force=False: 0)

    recommendation_calls: list[dict[str, object]] = []

    def fake_recommend(
        goal: str,
        top_k: int = 5,
        model_provider: str | None = None,
        model: str | None = None,
    ) -> list[dict[str, object]]:
        recommendation_calls.append({
            "goal": goal,
            "top_k": top_k,
            "model_provider": model_provider,
            "model": model,
        })
        return [{"name": "text-to-cad", "type": "harness", "score": 0.8}]

    monkeypatch.setattr(
        ci,
        "recommend_harnesses",
        fake_recommend,
    )

    rc = ci.main([
        "--model-mode", "custom",
        "--model", "openai/gpt-5.5",
        "--goal", "turn text prompts into CAD",
    ])

    assert rc == 0
    profile = json.loads((tmp_path / "ctx-model-profile.json").read_text())
    assert profile["mode"] == "custom"
    assert profile["provider"] == "openai"
    assert profile["model"] == "openai/gpt-5.5"
    assert profile["api_key_env"] == "OPENAI_API_KEY"
    assert recommendation_calls[0]["model_provider"] == "openai"
    assert recommendation_calls[0]["model"] == "openai/gpt-5.5"
    assert "text-to-cad" in capsys.readouterr().out


def test_main_custom_model_records_structured_harness_requirements(
    tmp_path: Path,
    monkeypatch,
) -> None:
    monkeypatch.setattr(ci, "_claude_dir", lambda: tmp_path)
    monkeypatch.setattr(ci, "seed_toolboxes", lambda force=False: 0)
    recommendation_calls: list[dict[str, object]] = []

    def fake_recommend(
        goal: str,
        top_k: int = 5,
        model_provider: str | None = None,
        model: str | None = None,
    ) -> list[dict[str, object]]:
        recommendation_calls.append({
            "goal": goal,
            "top_k": top_k,
            "model_provider": model_provider,
            "model": model,
        })
        return []

    monkeypatch.setattr(ci, "recommend_harnesses", fake_recommend)

    rc = ci.main([
        "--model-mode", "custom",
        "--model", "openai/gpt-5.5",
        "--goal", "build a code agent",
        "--harness-runtime", "windows python",
        "--harness-autonomy", "supervised",
        "--harness-tools", "filesystem shell browser",
        "--harness-verify", "pytest ruff",
        "--harness-privacy", "private repo no secrets",
        "--harness-attach-mode", "mcp",
    ])

    assert rc == 0
    profile = json.loads((tmp_path / "ctx-model-profile.json").read_text())
    assert profile["harness_requirements"] == {
        "runtime": "windows python",
        "autonomy": "supervised",
        "tools": "filesystem shell browser",
        "verification": "pytest ruff",
        "privacy": "private repo no secrets",
        "attach_mode": "mcp",
    }
    query = str(recommendation_calls[0]["goal"])
    assert "windows python" in query
    assert "filesystem shell browser" in query
    assert "pytest ruff" in query
    assert "private repo no secrets" in query
    assert "mcp" in query


def test_main_custom_model_no_fit_points_to_harness_plan(
    tmp_path: Path,
    monkeypatch,
    capsys,
) -> None:
    monkeypatch.setattr(ci, "_claude_dir", lambda: tmp_path)
    monkeypatch.setattr(ci, "seed_toolboxes", lambda force=False: 0)
    monkeypatch.setattr(ci, "recommend_harnesses", lambda *args, **kwargs: [])

    rc = ci.main([
        "--model-mode", "custom",
        "--model", "ollama/llama3.1",
        "--model-provider", "ollama",
        "--goal", "private local CAD workflow",
        "--harness-runtime", "linux server",
        "--harness-tools", "filesystem shell",
        "--harness-verify", "pytest",
        "--harness-privacy", "offline source code",
        "--harness-attach-mode", "mcp",
    ])

    assert rc == 0
    output = capsys.readouterr().out
    assert "no harness recommendations matched yet" in output
    assert "ctx-harness-install --recommend" in output
    assert "--model-provider \"ollama\"" in output
    assert "--harness-runtime \"linux server\"" in output
    assert "--harness-tools \"filesystem shell\"" in output
    assert "--harness-verify \"pytest\"" in output
    assert "--harness-privacy \"offline source code\"" in output
    assert "--harness-attach-mode \"mcp\"" in output
    assert "--plan-on-no-fit" in output


def test_recommend_harnesses_uses_wiki_frontmatter_for_fit(
    tmp_path: Path,
    monkeypatch,
) -> None:
    wiki = tmp_path / "wiki"
    page = wiki / "entities" / "harnesses" / "text-to-cad.md"
    page.parent.mkdir(parents=True)
    page.write_text(
        """---
title: Text to CAD
type: harness
tags:
  - cad
runtimes:
  - python
model_providers:
  - openai
capabilities:
  - Generate CAD artifacts from natural language prompts
    with OpenSCAD and mesh validation
repo_url: https://github.com/earthtojake/text-to-cad
---
# Text to CAD
""",
        encoding="utf-8",
    )
    graph = nx.Graph()
    graph.add_node(
        "harness:text-to-cad",
        label="text-to-cad",
        type="harness",
        tags=["cad"],
    )
    monkeypatch.setattr(ci, "_load_recommendation_graph", lambda: graph)
    import ctx_config

    monkeypatch.setattr(
        ctx_config,
        "cfg",
        SimpleNamespace(
            wiki_dir=wiki,
            claude_dir=tmp_path / ".claude",
            recommendation_top_k=5,
            harness_recommendation_min_fit_score=0.85,
        ),
    )

    results = ci.recommend_harnesses(
        "turn text prompts into CAD openscad openai gpt-5 harness",
        model_provider="openai",
        model="openai/gpt-5.5",
    )

    assert results
    assert results[0]["name"] == "text-to-cad"
    assert results[0]["fit_score"] >= 0.85
    assert "openai" in results[0]["fit_signals"]
    assert "gpt-5" not in results[0]["fit_signals"]
    assert "gpt-5" not in results[0]["missing_signals"]
    assert "openscad" in results[0]["fit_signals"]


def test_load_recommendation_graph_uses_configured_wiki_dir(
    tmp_path: Path,
    monkeypatch,
) -> None:
    wiki = tmp_path / "custom-wiki"
    out = wiki / "graphify-out"
    out.mkdir(parents=True)
    graph = nx.Graph()
    graph.add_node("harness:custom", label="custom", type="harness")
    data = nx.node_link_data(graph)
    (out / "graph.json").write_text(json.dumps(data), encoding="utf-8")

    import ctx_config

    monkeypatch.setattr(ctx_config, "cfg", SimpleNamespace(wiki_dir=wiki))

    loaded = ci._load_recommendation_graph()

    assert "harness:custom" in loaded


def test_recommend_harnesses_surfaces_reliability_rubric(
    tmp_path: Path,
    monkeypatch,
) -> None:
    wiki = tmp_path / "wiki"
    harness_dir = wiki / "entities" / "harnesses"
    harness_dir.mkdir(parents=True)
    (harness_dir / "reliable-agent.md").write_text(
        """---
title: Reliable Agent
type: harness
tags:
  - agents
model_providers:
  - openai
capabilities:
  - Persistent project context and task state
  - Permission limits, sandbox rules, and policy checks
  - Automated tests, evals, retry loops, and validation gates
verify_commands:
  - pytest
repo_url: https://example.test/reliable-agent
---
# Reliable Agent
""",
        encoding="utf-8",
    )
    graph = nx.Graph()
    graph.add_node(
        "harness:reliable-agent",
        label="reliable-agent",
        type="harness",
        tags=["agents"],
    )
    monkeypatch.setattr(ci, "_load_recommendation_graph", lambda: graph)
    import ctx_config

    monkeypatch.setattr(
        ctx_config,
        "cfg",
        SimpleNamespace(
            wiki_dir=wiki,
            claude_dir=tmp_path / ".claude",
            recommendation_top_k=5,
            harness_recommendation_min_fit_score=0.20,
            harness_reliability_weights={
                "context": 0.34,
                "constraints": 0.33,
                "convergence": 0.33,
            },
        ),
    )

    results = ci.recommend_harnesses(
        "openai agent workflow with tests and sandbox",
        model_provider="openai",
        model="openai/gpt-5.5",
    )

    assert results
    recommendation = results[0]
    assert recommendation["name"] == "reliable-agent"
    assert recommendation["reliability_score"] >= 0.90
    assert set(recommendation["reliability_dimensions"]) == {
        "context",
        "constraints",
        "convergence",
    }
    assert recommendation["reliability_dimensions"]["context"]["matched_terms"]
    assert recommendation["reliability_dimensions"]["constraints"]["matched_terms"]
    assert recommendation["reliability_dimensions"]["convergence"]["matched_terms"]
    assert "context" in recommendation["reliability_reason"]
    assert "constraints" in recommendation["reliability_reason"]
    assert "convergence" in recommendation["reliability_reason"]


def test_recommend_harnesses_prefers_reliable_harness_when_fit_ties(
    tmp_path: Path,
    monkeypatch,
) -> None:
    wiki = tmp_path / "wiki"
    harness_dir = wiki / "entities" / "harnesses"
    harness_dir.mkdir(parents=True)
    (harness_dir / "thin-agent.md").write_text(
        """---
title: Thin Agent
type: harness
tags:
  - agents
model_providers:
  - openai
capabilities:
  - Agent workflow orchestration
repo_url: https://example.test/thin-agent
---
# Thin Agent
""",
        encoding="utf-8",
    )
    (harness_dir / "reliable-agent.md").write_text(
        """---
title: Reliable Agent
type: harness
tags:
  - agents
model_providers:
  - openai
capabilities:
  - Agent workflow orchestration
  - Persistent context state and durable task documents
  - Permission limits, sandbox boundaries, and approval policies
  - Automated tests, evals, validation gates, and retry loops
verify_commands:
  - pytest
repo_url: https://example.test/reliable-agent
---
# Reliable Agent
""",
        encoding="utf-8",
    )
    graph = nx.Graph()
    for slug in ("thin-agent", "reliable-agent"):
        graph.add_node(
            f"harness:{slug}",
            label=slug,
            type="harness",
            tags=["agents"],
        )
    monkeypatch.setattr(ci, "_load_recommendation_graph", lambda: graph)
    import ctx_config

    monkeypatch.setattr(
        ctx_config,
        "cfg",
        SimpleNamespace(
            wiki_dir=wiki,
            claude_dir=tmp_path / ".claude",
            recommendation_top_k=5,
            harness_recommendation_min_fit_score=0.20,
            harness_reliability_weights={
                "context": 0.34,
                "constraints": 0.33,
                "convergence": 0.33,
            },
        ),
    )

    results = ci.recommend_harnesses(
        "openai agent workflow",
        model_provider="openai",
        model="openai/gpt-5.5",
    )

    assert [row["name"] for row in results[:2]] == [
        "reliable-agent",
        "thin-agent",
    ]
    assert results[0]["fit_score"] == results[1]["fit_score"]
    assert results[0]["reliability_score"] > results[1]["reliability_score"]


def test_recommend_harnesses_avoids_semantic_model_load_by_default(
    tmp_path: Path,
    monkeypatch,
) -> None:
    graph = nx.Graph()
    graph.add_node("harness:langgraph", label="langgraph", type="harness")
    monkeypatch.setattr(ci, "_load_harness_recommendation_graph", lambda: graph)
    monkeypatch.setattr(ci, "_harness_supports_provider", lambda *args, **kwargs: True)
    monkeypatch.setattr(ci, "_installed_harness_slugs", lambda _path: set())
    monkeypatch.setattr(
        ci,
        "_annotate_harness_fit",
        lambda *_args, **_kwargs: {"fit_score": 0.99, "fit_signals": ["agent"]},
    )
    import ctx_config

    monkeypatch.setattr(
        ctx_config,
        "cfg",
        SimpleNamespace(
            claude_dir=tmp_path / ".claude",
            recommendation_top_k=5,
            harness_recommendation_min_fit_score=0.85,
        ),
    )
    calls: dict[str, object] = {}

    def fake_recommend_by_tags(*_args, **kwargs):
        calls.update(kwargs)
        return [{"name": "langgraph", "type": "harness", "score": 1.0}]

    monkeypatch.setitem(
        sys.modules,
        "ctx.core.resolve.recommendations",
        type(
            "FakeRecommendModule",
            (),
            {
                "query_to_tags": staticmethod(lambda _query: ["agent"]),
                "recommend_by_tags": staticmethod(fake_recommend_by_tags),
            },
        ),
    )

    results = ci.recommend_harnesses(
        "build an agent workflow",
        model_provider="openai",
        model="openai/gpt-5.5",
    )

    assert results[0]["name"] == "langgraph"
    assert calls["query"] == "build an agent workflow"
    assert calls["entity_types"] == ("harness",)
    assert calls["use_semantic_query"] is False


def test_main_custom_model_requires_model(tmp_path: Path, monkeypatch) -> None:
    monkeypatch.setattr(ci, "_claude_dir", lambda: tmp_path)
    monkeypatch.setattr(ci, "seed_toolboxes", lambda force=False: 0)

    assert ci.main(["--model-mode", "custom"]) == 1


def test_validate_model_flag_invokes_connection_check(
    tmp_path: Path,
    monkeypatch,
) -> None:
    monkeypatch.setattr(ci, "_claude_dir", lambda: tmp_path)
    monkeypatch.setattr(ci, "seed_toolboxes", lambda force=False: 0)
    monkeypatch.setattr(
        ci,
        "recommend_harnesses",
        lambda goal, top_k=5, model_provider=None, model=None: [],
    )
    calls: list[dict] = []

    def fake_validate(**kwargs):
        calls.append(kwargs)
        return 0

    monkeypatch.setattr(ci, "validate_model_connection", fake_validate)

    rc = ci.main([
        "--model-mode", "custom",
        "--model", "ollama/llama3.1",
        "--validate-model",
    ])

    assert rc == 0
    assert calls == [{
        "model": "ollama/llama3.1",
        "api_key_env": None,
        "base_url": None,
    }]