| --- |
| pretty_name: SecondState FAB — Agent Traces and Grading |
| language: |
| - en |
| license: cc-by-4.0 |
| size_categories: |
| - n<1K |
| task_categories: |
| - question-answering |
| tags: |
| - finance |
| - financial-due-diligence |
| - benchmark |
| - agents |
| - agent-traces |
| - tool-use |
| - evaluation |
| - synthetic |
| configs: |
| - config_name: default |
| data_files: |
| - split: test |
| path: data/*.parquet |
| --- |
| |
| # FAB — Agent Traces and Grading |
|
|
| **600 completed agent runs: four models × 50 tasks × three trials.** |
| Agents investigate a synthetic company's data room and answer financial |
| due-diligence questions. Each row pairs a full execution trace with the task, |
| final answer, grading criteria, pass/fail verdicts and judge explanations. |
| Tasks 041 and 049 are included. |
|
|
| The [benchmark dataset](https://huggingface.co/datasets/secondstate/finance-agents-benchmark) |
| contains the shared data room and tasks. The |
| [GitHub repository](https://github.com/SecondState-ai/finance-agents-benchmark) |
| contains the execution and grading harness. |
|
|
| ## Use |
|
|
| ```python |
| import json |
| from datasets import load_dataset |
| |
| runs = load_dataset( |
| "secondstate/finance-agents-benchmark-traces", revision="v1.0", split="test" |
| ) |
| run = runs[0] |
| events = [json.loads(line) for line in run["trace_jsonl"].splitlines()] |
| grades = run["grades"] |
| ``` |
|
|
| `trace_jsonl` contains the complete original JSONL trace as a string, preserving |
| provider-specific event fields. `grades` is a list of criterion IDs, titles, |
| rubric text (`match_criteria`), verdicts and judge explanations (`reasoning`). |
| The explanations describe grading decisions; they are separate from agent events. |
|
|
| | Fields | Contents | |
| | --- | --- | |
| | `run_id`, `model`, `trial`, `task_id`, `difficulty` | Stable run identity and filters | |
| | `task_title`, `instructions`, `response` | Agent request and original answer | |
| | `all_pass`, `criteria_passed`, `criteria_total`, `criterion_pass_rate`, `grades` | Final grading | |
| | `trace_jsonl`, `trace_event_count`, `agent_turns`, `tool_calls` | Full trace and execution counts | |
| | `*_path`, `*_sha256`, `judge_model` | Original artifacts and provenance | |
|
|
| To download all original artifacts: |
|
|
| ```bash |
| hf download secondstate/finance-agents-benchmark-traces \ |
| --repo-type dataset --revision v1.0 --local-dir ./fab-traces |
| ``` |
|
|
| `runs/<model>/trial-<NN>/<task>/` contains `response.md`, final `scores.json`, |
| original `run.json` and `task.json`, plus `transcript.jsonl.gz` and |
| `metrics.json.gz`. Use `gzip -dc <file.gz>` to read compressed files. |
| Final grading rubrics are in `grading-tasks/`; aggregate results and usage are in |
| [reports](reports). [manifest.json](manifest.json) records file hashes. |
|
|
| ## Grading and scope |
|
|
| The judge is `gpt-6-luna` at maximum reasoning. A task passes only if every |
| criterion passes. Grades come from the full regrade completed on 27 September |
| 2026, covering all 600 answers; these are existing evaluations, not new runs. |
|
|
| | Model | Task pass rate | Criterion pass rate | |
| | --- | ---: | ---: | |
| | DeepSeek V4.1 Flash | 60.0% | 81.0% | |
| | GPT-6 Sol | 58.7% | 83.4% | |
| | GPT-6 Luna | 50.7% | 79.5% | |
| | GLM 5.3 Flash | 47.3% | 76.2% | |
|
|
| Original run snapshots and final grading rubrics are both retained. Agent |
| instructions are unchanged; some rubric criteria were clarified before the |
| full regrade. Grading criteria were kept outside the agent workspace. |
| Answers, metadata and traces preserve their original bytes; final score files |
| omit the local `source_run` path. Failed attempts, scratch files and intermediate |
| grading checkpoints are excluded. Results describe one synthetic company. |
|
|
| Source: [published runs at commit 4c78c7c](https://github.com/SecondState-ai/finance-agents-benchmark/tree/4c78c7cc59f3667a62343c1a9a55f91ea565bd7d/results/published). |
| License: [CC BY 4.0](LICENSE). Cite SecondState's |
| [Finance Agents Benchmark](https://github.com/SecondState-ai/finance-agents-benchmark) |
| and the dataset revision when reusing these results. |
|
|
