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benchmark-evaluation

benchmark-evaluation

【数据与研究】Validate DeepResearch benchmark rollout files and choose official evaluation routes before spending judge API credits.

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技能说明

GitHub

name: benchmark-evaluation description: "Validate DeepResearch benchmark rollout files and choose official evaluation routes before spending judge API credits." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Benchmark Evaluation

Use this sub-skill when a future agent already has DeepResearch prediction rollout files and needs to decide whether they are ready for official LLM-as-judge evaluation. It is a guidance and preflight skill: it does not generate predictions and it does not call external judge APIs.

Route to this sub-skill when

  • The task mentions evaluate_deepsearch_official.py, evaluate_hle_official.py, pass@k, HLE, GAIA, BrowseComp, WebWalker, XBench DeepSearch, scored JSONL, or judge-model costs.
  • A rollout folder contains iter1.jsonl, iter2.jsonl, iter3.jsonl, or split-suffixed files such as iter2_split3of8.jsonl.
  • The user wants to inspect malformed JSONL, missing predictions/messages, invalid <answer>...</answer> tags, missing round files, or termination frequencies before running official judging.

Do not use this sub-skill for

  • Creating DeepResearch predictions or running the ReAct agent; route to the sibling react-inference sub-skill.
  • Choosing among WebAgent family projects or understanding their project-specific evaluators; route to webagent-family, then return here for common rollout and LLM-judge concepts.
  • Replacing the official judge scripts. The bundled validator is a safe schema preflight only, not an implementation of official benchmark metrics.

Fast safe preflight

From this sub-skill directory, validate an unsplit DeepResearch rollout folder:

python scripts/validate_prediction_rollouts.py <rollout-folder> --dataset gaia

Validate distributed rollouts written by run_multi_react.py --total_splits N:

python scripts/validate_prediction_rollouts.py <rollout-folder> --dataset webwalker --allow-splits

Validate an HLE single JSONL file before the HLE judge route:

python scripts/validate_prediction_rollouts.py <hle-predictions.jsonl> --dataset hle

A passing validator result means the files satisfy local shape checks. It does not mean the official LLM judge has run or that pass@k metrics are available.

Read next

  • references/prediction-format.md for rollout file names, fields, split behavior, and validator interpretation.
  • references/evaluation-workflows.md for official DeepSearch and HLE evaluator routes, judge-model selection, metrics, and output files.
  • references/troubleshooting.md for missing rounds, malformed JSON, absent fields, invalid answer tags, unsupported datasets, missing API variables, and tokenizer caveats.
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