claude

evals

AI Operations Team — Evals: Eval harness design, benchmark suites, automated regression, human eval orchestration.

77 on GitHubby tonone-aiv1.20.0MITupdated 2 days ago
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Plugin evals from marketplace tonone-ai in tonone-ai/tonone. Commands read from the repo's manifest — 2 days ago.

What it installs

Skills (5)

  • evals-analyze

    Analyze LLM eval results — score breakdowns by category, regression detection vs baseline, failure clustering. Use when asked to "analyze our eval results", "did the model regress", or "cluster the eval failures".

  • evals-design

    Design an LLM eval — task schema, scoring rubric, dataset composition, and pass/fail thresholds. Use when asked to "design an LLM eval", "write a scoring rubric", or "how do we measure this model".

  • evals-harness

    Design eval harnesses — task schemas, metrics, dataset versioning, eval-as-code patterns. Use when asked to "build an eval harness", "set up eval-as-code", or "version our eval datasets".

  • evals-recon

    Audit existing eval coverage — gaps, metric validity, benchmark leakage, dataset freshness. Use when asked "what eval coverage do we have", "audit our evals", or "check for benchmark leakage".

  • evals-regress

    Build automated regression suites — golden sets, threshold alerting, CI integration for model changes. Use when asked to "catch model regressions in CI", "build a golden set", or "automate eval regression".

Subagents (1)

  • evals

    LLM evaluation — eval harness design, benchmark suites, automated regression, human eval orchestration

View source on GitHub second.tonone.ai

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