Eval Audit

ai-evals-course/evals-skills

Audit an LLM evaluation pipeline for missing error analysis, unvalidated judges, data leakage and stale checks.

Contenu mis à jour:

Dans la collectionAI Evals Skills ↗
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npx skills add ai-evals-course/evals-skills --skill eval-audit
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Install and use Eval Audit

  1. Install the Skill

    Run the upstream command in your project, then follow the author’s setup guide and any requirements below.

    npx skills add ai-evals-course/evals-skills --skill eval-audit
  2. Give your agent a task

    Provide the relevant files, context and constraints. For example:

    Audit these evaluation datasets, judge instructions and reports for leakage, missing validation and stale checks.

À propos de ce Skill

Audit an LLM evaluation pipeline for missing error analysis, unvalidated judges, data leakage and stale checks.

Pourquoi ce choix

A focused audit of product evaluation artifacts, including judge validation against human labels.

À quoi il sert

  • Review an existing LLM evaluation system and prioritize evidence-backed improvements.

How it works and limitations

The result is an audit and prioritized recommendations, not proof that a judge is calibrated. Other tasks in the repository cover building and validating evaluators.

Avant de l’utiliser

  • Provide evaluation traces, judge prompts, labeled data or other pipeline artifacts; an observability integration is optional.

Sources et références

Les sources originales sont liées ci-dessous. Les pistes pratiques sont des suggestions de la rédaction de SkillHey.