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15
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int64
3
20
n_tool_calls
int64
0
20
n_malformed
int64
0
7
n_tool_errors
int64
0
7
prompt_tokens
int64
1.55k
664k
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int64
401
38.9k
seed_ref
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4
117
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2 classes
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b1c_1001
B1C
done
18
16
1
2
446,054
15,165
1001
true
"Survey client 1001 across the firm's DMS. All of this client's matters live under matters/1001-*. I(...TRUNCATED)
[{"role":"system","content":"You are an agent exploring the document management system (DMS) of the (...TRUNCATED)
b1c_1002
B1C
done
8
6
1
0
108,684
9,371
1002
true
"Survey client 1002 across the firm's DMS. All of this client's matters live under matters/1002-*. I(...TRUNCATED)
[{"role":"system","content":"You are an agent exploring the document management system (DMS) of the (...TRUNCATED)
b1c_1003
B1C
done
15
14
0
1
351,491
6,710
1003
true
"Survey client 1003 across the firm's DMS. All of this client's matters live under matters/1003-*. I(...TRUNCATED)
[{"role":"system","content":"You are an agent exploring the document management system (DMS) of the (...TRUNCATED)
b1c_1004
B1C
done
9
8
0
0
107,483
7,136
1004
true
"Survey client 1004 across the firm's DMS. All of this client's matters live under matters/1004-*. I(...TRUNCATED)
[{"role":"system","content":"You are an agent exploring the document management system (DMS) of the (...TRUNCATED)
b1c_1005
B1C
done
14
12
1
0
337,421
11,345
1005
true
"Survey client 1005 across the firm's DMS. All of this client's matters live under matters/1005-*. I(...TRUNCATED)
[{"role":"system","content":"You are an agent exploring the document management system (DMS) of the (...TRUNCATED)
b1c_1006
B1C
done
13
12
0
0
251,908
8,163
1006
true
"Survey client 1006 across the firm's DMS. All of this client's matters live under matters/1006-*. I(...TRUNCATED)
[{"role":"system","content":"You are an agent exploring the document management system (DMS) of the (...TRUNCATED)
b1c_1007
B1C
done
14
12
1
0
300,385
14,934
1007
true
"Survey client 1007 across the firm's DMS. All of this client's matters live under matters/1007-*. I(...TRUNCATED)
[{"role":"system","content":"You are an agent exploring the document management system (DMS) of the (...TRUNCATED)
b1c_1008
B1C
done
13
12
0
0
285,475
9,347
1008
true
"Survey client 1008 across the firm's DMS. All of this client's matters live under matters/1008-*. I(...TRUNCATED)
[{"role":"system","content":"You are an agent exploring the document management system (DMS) of the (...TRUNCATED)
b1c_1009
B1C
done
12
11
0
0
265,753
9,665
1009
true
"Survey client 1009 across the firm's DMS. All of this client's matters live under matters/1009-*. I(...TRUNCATED)
[{"role":"system","content":"You are an agent exploring the document management system (DMS) of the (...TRUNCATED)
b1c_1010
B1C
done
9
8
0
0
147,117
8,341
1010
true
"Survey client 1010 across the firm's DMS. All of this client's matters live under matters/1010-*. I(...TRUNCATED)
[{"role":"system","content":"You are an agent exploring the document management system (DMS) of the (...TRUNCATED)
End of preview. Expand in Data Studio

C&H Trajectory Pool — Qwen3.5-4B (on-policy)

1,376 agentic exploration trajectories over the full Calderwood & Harkness (C&H) synthetic law-firm corpus (266 matters, ~145M tokens; the open-sourced world from harvey-labs tasks/firm-knowledge/, MIT), generated by Qwen/Qwen3.5-4B — the same model intended as the training student, so this pool is exactly on-policy for it. Part of a world-internalization research project: which likelihood targets, derived from agent experience, internalize a world into model weights.

Companion datasets under this namespace: ch-pilot-rollouts-qwen3.5-35b-a3b and ch-pilot-rollouts-qwen3.5-9b (20-rollout actor-selection pilot).

Task mix (1,376 = one identical, seed-matched spec set)

  • B1 (266) — one survey per matter: client, parties, timeline, events, status, key documents; path citations required for every claim.
  • B1C (46) — one survey per client: cross-matter dossier.
  • B2 (1,064) — self-QA, 4 per matter: given a 2,000-char excerpt from a sampled seed document, pose 3 nontrivial questions (single-doc / cross-doc / cross-matter) and answer them with tools; answers must cite at least one non-seed file, and the cross-matter answer files from ≥2 matters.

Protocol

Text-based tools (glob / grep / read) over a markdown mirror of the corpus, one call per turn as <tool>{json}</tool>, observations returned in <tool_result> (16,000 chars max), answers in <final>...</final>, temperature 0.7, ≤20 turns, 65,536-token context. Generation was mechanically gated (this matters for data quality):

  • a </tool> stop-sequence ends each turn at the tool call (no runaway generation);
  • a <final> is accepted only if closed, ≥50 chars, and after ≥1 successful tool call — otherwise the driver returns a corrective error (3 strikes → protocol_failure);
  • near the context budget (~50k tokens) or turn cap, tool access ends and the model is told to write its final from what it already read (graceful wrap-up instead of overflow loss).

Composition

status n
done (all usable: ≥1 tool call, closed substantive final) 1,353 (98.3%)
protocol_failure 14
max_turns 7
api_error 2

Each row: full message history (messages: system / user / assistant / tool), run metadata (mode, status, turn/call/error counts, token usage, seed_ref), and a precomputed usable flag. Assistant turns include the model's reasoning text.

Provenance & license

All document content is synthetic (no real firm, clients, or people), derived from Harvey AI's MIT-licensed harvey-labs release (commit 7be41d5); trajectories released under MIT. The 250 firm-knowledge eval tasks are not used or contained here — they remain a held-out evaluation set.

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