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result-logging

result-logging

Understand, validate, summarize, compare, and safely route lm-evaluation-harness result artifacts, sample logs, cache files, and optional external logging integrations.

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name: result-logging description: "Understand, validate, summarize, compare, and safely route lm-evaluation-harness result artifacts, sample logs, cache files, and optional external logging integrations." disable-model-invocation: true metadata: disco-role: operating license: MIT

Result Logging

Use this sub-skill when the user needs help interpreting saved lm-eval outputs, validating result JSON, comparing finished runs, preparing logging arguments, or converting local result files into tables.

Route Here For

  • Reading aggregated results_*.json files and optional per-task samples_*.jsonl logs.
  • Explaining result schema fields such as results, groups, configs, versions, n-shot, higher_is_better, n-samples, samples, config, task_hashes, tokenizer metadata, and environment metadata.
  • Debugging why metrics, sample logs, task hashes, stderr values, cache files, or service uploads are missing.
  • Preparing --output_path, --log_samples, --predict_only, --wandb_args, --trackio_args, and --hf_hub_log_args without exposing credentials.
  • Summarizing or comparing already-saved local JSON results with bundled scripts.
  • Planning Zeno visualization prerequisites without assuming a network service or API key is available.

Do Not Use For

  • Constructing and running new evaluations; route to ../evaluation-runs/.
  • Choosing or configuring model backends; route to ../model-backends/.
  • Defining task metrics or YAML task behavior; route to ../task-authoring/.
  • Running network uploads to W&B, Trackio Spaces, Hugging Face Hub, or Zeno unless the user explicitly asks and provides safe credential handling.

Fast Paths

  • Result schema: read references/result-schema.md.
  • Logging workflows, table generation, result comparison, service arguments, cache notes, and Zeno prerequisites: read references/result-workflows.md.
  • Failure diagnosis: read references/troubleshooting.md.
  • Local table from one or more result JSON files:
    python scripts/summarize_results.py path/to/results.json
    
  • Local metric comparison between two saved runs:
    python scripts/compare_results.py run_a.json run_b.json --metric acc
    

Safety Defaults

  • Treat result files as local artifacts; do not publish, upload, or create repos unless the user explicitly asks.
  • Never print tokens from HF_TOKEN, W&B, Trackio, Zeno, or config files.
  • Prefer local JSON validation and summaries before diagnosing backend or task behavior.
  • If predict_only is used, expect predictions/sample logs but no aggregate metrics.
  • If log_samples is requested, require an output_path; sample logs are not useful if they are never written.
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