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eval_run_guard

中文 · Product specification · Contributing · Security

Privacy-first offline integrity checks for agent evaluation JSONL runs.

Evaluation pipelines often finish successfully while leaving malformed records, duplicate sample IDs, conflicting terminal states, invalid scores, or stale aggregate summaries. eval_run_guard checks those concrete failure modes without learning a framework-specific schema or exposing evaluation content.

Install

Download a release archive, or build with Rust 1.85 or newer:

cargo install --path . --locked

Use

Create a small mapping file:

{
  "sample_id": "sample.id",
  "status": "result.status",
  "score": "result.score",
  "score_min": 0.0,
  "score_max": 1.0,
  "summary": {
    "total": "counts.total",
    "completed": "counts.completed",
    "errored": "counts.errored",
    "scored": "counts.scored",
    "mean": "score.mean"
  }
}

Audit a JSONL run, optionally reconciling a separate summary:

eval_run_guard audit run.jsonl --config mapping.json --summary summary.json
eval_run_guard audit run.jsonl --config mapping.json --format json
eval_run_guard audit run.jsonl --config mapping.json --format sarif > results.sarif

Exit code 0 means no findings, 1 means findings were reported, and 2 means the input or invocation could not be audited.

Guarantees and limits

  • Reads explicit, stable local regular files only. Symlink rejection is best-effort validation, not a hostile concurrent-filesystem security boundary.
  • Streams JSONL with explicit limits for records, fields, tracking memory, and findings.
  • Reports fixed explanations, sanitized basenames, and line numbers—not sample IDs, values, content, or absolute paths.
  • Recomputes only declared counts and an arithmetic mean.
  • Does not infer schemas, run evaluations, repair files, or access the network.

See the product specification for exact finding codes and semantics.

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License

MIT

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Offline integrity checks for AI evaluation run artifacts and summaries.

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