eval-skills

AI Agent Skill unit testing framework — a framework-agnostic toolkit for discovering, scaffolding, selecting, evaluating, and reporting on AI skills.

This skill fills the L1 (Skill Unit Test) gap that LangSmith / DeepEval leave open: while those platforms focus on agent-level and trajectory-level evaluation (L2-L3), eval-skills targets the individual skill level, ensuring each building block meets quality standards before it ever enters an agent pipeline.

When to Use This Skill

Before deploying a new skill to production — run eval to verify it meets your quality gate.
When choosing between multiple candidate skills — run select to rank them on the same benchmark.
When a skill is upgraded — run report diff to detect regressions.
In CI/CD — use --exit-on-fail to block merges that degrade skill quality.
When bootstrapping a new skill — run create to generate a ready-to-fill skeleton.

Capabilities

1. Find Skills

Search for existing skills by keyword, tag, or adapter type.