# Trajectory source inventory Audit date: 2026-10-14. Counts below distinguish upstream rows, imported canonical records and records passing the strict multi-action/context gate. `data/coverage/trajectory_sources.json` is the machine-readable counterpart; `data/library/manifest.json` hashes every local canonical shard. “Complete import” means the full identified upstream population for that release/split, not every artifact ever published for a benchmark. “Protected” means usable for evaluation/inspection but blocked from training export. Source outcomes were not independently replayed unless explicitly stated. > **Release note:** the detailed sections below document the original v0.3.0 > build. The append-only v0.4.0 release expands the inventory from 155,278 to > 235,876 trajectories without rebuilding those records. See the > [v0.4.0 incremental audit](v0.4.0_incremental_audit.md) for its pinned > sources, accepted/rejected counts, rights decisions and exact append command. ## Measured coverage `Imported` counts successfully canonicalized source rows before exact deduplication. `Canonical` collapses only records with the same causal interaction **and** the same outcome/reward/completeness/verification evidence; all contributing IDs and locators remain in `duplicate_provenance.jsonl.gz`. S/F/U are canonical success/failure/unknown counts. `Strict` is the retained canonical count passing the complete multi-action/context gate. | Source | Upstream rows | Imported | Canonical | Unique tasks | Strict | S/F/U | Missing or collapsed | |---|---:|---:|---:|---:|---:|---:|---| | SWE-Gym OpenHands SFT | 491 | 491 | 491 | 293 | 491 | 491/0/0 | none | | SWE-Gym Sampled | 6,055 | 6,055 | 5,502 | 2,438 | 5,502 | 491/5,011/0 | 553 identical records collapsed | | SWE-bench Verified trajectories | 5,000 | 5,000 | 4,544 | 500 | 4,532 | 3,392/1,152/0 | 456 identical records collapsed; 12 retained partials | | SWE-bench Multilingual trajectories | 129 | 129 | 129 | 43 | 110 | 8/121/0 | 19 retained partials | | SWE-smith `tool` | 24,100 | 24,100 | 24,100 | 10,637 | 24,100 | 9,427/14,673/0 | alternate XML/ticks serializations excluded | | NVIDIA v1.2/OpenHands | 677,815 all-release | 51,626 | 51,626 | 33,444 | 51,626 | 24,743/26,883/0 | 626,189 other version/scaffold rows not imported | | Terminal-Bench trajectories | 52,104 | 34,462 | 34,263 | 89 | 24,086 | 11,051/23,212/0 | 17,642 have no steps; 199 identical records collapsed | | TerminalTraj | 20,000 | 20,000 | 20,000 | 17,787 | 19,143 | 0/0/20,000 | 857 retained short/partial traces | | AgentSuite τ² | 8,340 | 8,340 | 8,340 | 228 | 8,337 | 3,375/4,965/0 | 3 retained incomplete traces | | Official τ³ checked result | 200 | 200 | 200 | 50 | 0 | 100/100/0 | protected; not SFT-complete under strict gate | | BrowseComp rollouts | 5,064 | 5,063 | 5,063 | 1,266 | 5,063 | 1,211/3,852/0 | 1 malformed row | | Mind2Web exposed conversion | 1,009 | 1,009 | 1,009 | 1,009 | 1,009 | 0/0/1,009 | binary task outcome absent | | ToolBench checked examples | 15 | 11 | 11 | 11 | 0 | 7/4/0 | 4 fail final gate; source flags are not semantic proof | | AgentSuite BFCL | 115,466 | 0 | 0 | 0 | 0 | 0/0/0 | final calls only; no observations | | ALFWorld planner records | 7,080 | 0 | 0 | 0 | 0 | 0/0/0 | actions lack paired observations | Across the final inputs, 156,486 source rows became 155,278 canonical interactions after 1,208 exact duplicates were collapsed. They cover 67,610 normalized tasks; 143,999 interactions pass the strict gate and 110,208 are also training-eligible after protected-source separation. The coverage manifest additionally records official final-answer/task registries and the DeepSWE search result that do not enter this table as trajectory releases. ## SWE-Gym and SWE-bench family - [SWE-Gym OpenHands SFT](https://huggingface.co/datasets/SWE-Gym/OpenHands-SFT-Trajectories), revision `4aaa5a4a4b5861f4799d2336908760c190ac3b17`, MIT: all 491 `train.success.oss` OpenHands completion trajectories imported. The success label is the published split, not local replay. Messages encode tool actions/results in content; no arbitrary sample cap was used. - [SWE-Gym OpenHands Sampled](https://huggingface.co/datasets/SWE-Gym/OpenHands-Sampled-Trajectories), revision `baf3a4e4bff514d48ddc08a93a2ade5c126212c7`, no card license: all 6,055 attempts imported, including published successful and failed execution outcomes, structured tools and reports. - [tarsur385 SWE-bench Verified trajectories](https://huggingface.co/datasets/tarsur385/swebench-verified-trajectories), revision `773748a7c1222e8a642a7059821498e14293562a`, MIT: all 5,000 mini-SWE-agent files (10 model families × 500 protected tasks) imported. Calls, results and source-resolved verdicts are full trajectories; all remain protected evaluation data. The official SWE-bench Verified instance table contains issues/tests/gold patches, not trajectories. - [AlienKevin SWE-bench Multilingual trajectories](https://huggingface.co/datasets/AlienKevin/SWE-bench-Multilingual-trajectories), revision `7221c09c6cc0ed16d51c9cb9886a1ab484465670`, MIT: all 129 attempts (three models × 43 Rust tasks) imported; 110 pass the strict contextualized multi-action gate. The remaining 19 are explicit tier-5 partial/short diagnostics. This is a third-party protected rollout release, not an official expert-demonstration set. - [SWE-smith trajectories](https://huggingface.co/datasets/SWE-bench/SWE-smith-trajectories), revision `08e109b4a59eaeebf80e4675cd125d42e7ac99a4`, MIT: all 24,100 `tool` rows imported and accepted. The `xml` (26,076 rows) and `ticks` (25,826 rows) configurations are alternate serializations rather than additional independent rollouts, so they are deliberately not duplicated. ## NVIDIA Open-SWE-Traces [nvidia/Open-SWE-Traces](https://huggingface.co/datasets/nvidia/Open-SWE-Traces) was pinned at `6d0a83373ae0d83abe3d363f1f18cb1822e16586` (CC-BY-4.0). The release enumerates 677,815 trajectories: | Version | Rows | |---|---:| | v1.0 | 151,219 | | v1.1 | 263,226 | | v1.2 | 263,370 | | **All** | **677,815** | All 51,626 v1.2/OpenHands records across 24 revision-qualified source Parquet shards were imported and passed the action/observation gate. Messages, tools and metadata were JSON-decoded; native instance/model/scaffold/resolved fields remain intact. The other 626,189 version/scaffold rows were not downloaded: their source Parquet totals 55,056,684,304 bytes, which exceeds the remaining workspace budget once lossless canonical records and indexes are retained. This is an explicitly quantified partial import, not a sample represented as a complete NVIDIA corpus. The upstream repository advanced during the audit, but all imported URLs and metadata remained pinned to the stated SHA. ## Terminal agents - [yoonholee Terminal-Bench trajectories](https://huggingface.co/datasets/yoonholee/terminalbench-trajectories), revision `04e8940f5b6736a7ce8d22224fe2f2af74163ed2`, Apache-2.0: all 52,104 trial rows enumerated. Exactly 34,462 publish step sequences and were imported; 17,642 `steps=null` rows are rejected as absent trajectories. Of the deduplicated traces, 24,086 pass the strict gate and the rest remain tier-5 partial diagnostics. Model, scaffold, reward, duration, token and cost fields are preserved. Observations are source-truncated to 5,000 characters. This protected third-party release is distinct from the official task repo. - [TerminalTraj](https://huggingface.co/datasets/m-a-p/TerminalTraj), revision `5c1823f4a8b9ca0cf02c27d2db52c5b35b53a308`, no card license: all 20,000 command/output records imported; 19,143 pass the multi-action/context gate. No trustworthy task-level verdict exists, so outcomes are unknown—not failed. - The [official Terminal-Bench repository](https://github.com/laude-institute/terminal-bench) at `d28711d0da2675d0bb1d56de45ae5df6082438a3` contains 241 protected task manifests, tests and reference scripts. Those are not completion trajectories; 966 audited files carried explicit anti-training canaries. ## τ² and τ³ - [AgentSuite τ² trajectories](https://huggingface.co/datasets/AgentSuite/tau2-bench-trajectories), revision `07264f1d253a618fc20966670eddc44246212916`, no card license: all 8,340 rollouts (30 models × 278 task slots) imported; 8,337 pass the complete action/observation gate and three remain explicit incomplete diagnostics because a call has no returned observation. System/user/assistant/tool interactions and evaluator correctness/reward are present. Tool definitions are absent and declared missing. They are τ² rollouts, not assumed version-compatible with τ³. - [Official τ³ repository rollouts](https://github.com/sierra-research/tau2-bench), revision `dd8757d4c8791dad7b3cdaf02a105a3d5f9d86bd`, MIT code plus benchmark restrictions: the available checked-in final result file contains 200 model/user-simulator trials over 50 tasks (100 source successes and 100 failures). It is imported for evaluation only. Expected actions and solution metadata are never treated as expert demonstrations. ## Function calling and general tool use - [AgentSuite BFCL outputs](https://huggingface.co/datasets/AgentSuite/BFCL-trajectories), revision `a86612c6bb68e6566e5e7d206f7b031af889edc0`, no card license: all 115,466 rows were audited. They contain user prompts, model final function calls, scores and latency but no returned tool observations. Zero qualify as trajectories; none enter the canonical library. This is “exists but is only final output,” not “no BFCL data exists.” - [ToolBench](https://github.com/OpenBMB/ToolBench), revision `d56fdd89faf8c91fa135090b212bb9057ee5cfc2`, Apache-2.0 repository: all 15 checked-in answer examples were inspected, 13 adapted, and 11 pass the strict gate. The final cumulative history is used once; cumulative prefixes are not duplicated. `win`/`valid_data` are generation flags rather than independent semantic success evidence. A complete full-release population was not verified. ## Web agents - [rl-rag BrowseComp rollouts](https://huggingface.co/datasets/rl-rag/browsecomp-gpt-oss-120b-260222), revision `ac4854be0eb527cdf90f6c7d09446eeb7a3d1dbd`, no card license: 5,063/5,064 full research-agent conversations imported; one row lacks a conversation. The release normally has four GPT-OSS-120B attempts per question, full search results and a source GPT-4o answer-judge verdict. Reference answers stay out of model input. This is protected evaluation data; official BrowseComp question/answer rows alone are not trajectories. - [Mind2Web](https://huggingface.co/datasets/osunlp/Mind2Web), revision `17ece8eb89862368edc0cc806acee6fca5163474`, CC-BY-4.0: all 1,009 rows exposed by the hosted partial Parquet conversion imported. These are human action sequences with a full pre-action DOM for each target and no binary task-success field. Completeness is claimed only for that exposed conversion, not every historical artifact. ## ALFWorld and DeepSWE - [ALFWorld](https://github.com/alfworld/alfworld) release 0.2.2 contains 7,080 planner `traj_data.json` records (archive SHA-256 `25171f16e20ad7b048c47275c45b0babf3aa1cbab29cec97387922350a9844bc`). They preserve human task text, planner/low actions and image references but not action-paired environment observations in the audited artifact. They are therefore excluded rather than promoted to full trajectories. - No exact public, pinned DeepSWE/Datacurve full-trajectory release was found. This is the “none found after searching” state—not evidence that no private or future trajectory artifact exists. Protected SWE evaluation/reference data was not substituted for demonstrations. ## Outcome and permission interpretation - Expert provenance is used only for human/reference/planner demonstrations; successful model rollouts remain recorded agent completions. - Source-evaluator and source-reported verdicts are distinct from independent reproduction. This build performed zero native benchmark replays. - Conditional sources can populate preparation-time training exports because licensing was explicitly out of scope for this data-preparation task. Evaluation-only sources remain `protected_evaluation` regardless. - Failed and unknown outcomes have separate indexes and denominators. ## Reproducing imports Most hosted releases use the same resumable command (repeat `--split` for multi-split datasets): ```bash .venv/bin/python scripts/import_hf_release.py SOURCE_ID DATASET_ID \ --revision IMMUTABLE_SHA --output data/full/canonical/OUTPUT \ --cache data/cache/full/OUTPUT --config default --split SPLIT ``` Concrete source/split pairs are recorded in `data/registry/sources.json` and every generated `release-manifest.json`. NVIDIA uses pinned repository files so the moving dataset-server conversion cannot change the bytes: ```bash .venv/bin/python scripts/import_hf_release.py \ nvidia_open_swe_traces nvidia/Open-SWE-Traces \ --revision 6d0a83373ae0d83abe3d363f1f18cb1822e16586 \ --output data/full/canonical/nvidia_v1_2_openhands_original \ --cache data/cache/full/nvidia_v1_2_openhands_original \ --config v1.2 --split openhands \ --original-glob 'data/openhands/qwen38_27b/*/*.parquet' \ --original-glob 'data/openhands/qwen38_flash_next/*/*.parquet' ``` Native JSON trees (tarsur SWE-bench Verified, AgentSuite τ² and official τ³) are checked out at the registered SHA and streamed with: ```bash .venv/bin/python scripts/import_json_tree.py SOURCE_ID PINNED_CHECKOUT \ --output data/full/canonical/OUTPUT/all.jsonl.gz \ --revision IMMUTABLE_SHA --url DIRECT_SOURCE_URL --glob '**/*.json*' ``` The combined 211-record seed used by the final build is reproducible from the official τ³ result and checked-in ToolBench example. First adapt those pinned files separately; apply `scripts/filter_canonical.py --strict --source toolbench` to the ToolBench result (13 adapt, 11 pass); then combine the 200 τ³ and 11 ToolBench records with: ```bash .venv/bin/python scripts/filter_canonical.py \ data/full/canonical/official_tau3/all.jsonl.gz \ data/full/canonical/toolbench/strict.jsonl.gz \ --source official_tau3 --source toolbench \ --output data/full/canonical/seed_evaluation/official_tau3_toolbench.jsonl.gz ``` Finally run the complete-library, coverage, gallery and evaluation commands in the root [README](../README.md). No command applies an arbitrary row limit.