eval-skills

What problem does it solve?

This Skill automates discovery and quality auditing of SKILL.md and flat skill markdown files across a repository to identify missing frontmatter, improper allowed-tools scoping, inappropriate effort tags, and structural/content issues. It consolidates findings into a scored report and produces recommended effort-field patches so maintainers can quickly remediate inconsistencies.

Core Features & Use Cases

• Automated discovery of SKILL.md and flat .md skill files using filesystem globs and optional paths.
• Structured scoring across name, description, allowed-tools, effort, content structure, and bonus metadata with clear thresholds for pass/fail.
• Effort inference engine that suggests low/medium/high effort based on verbs, scope, allowed-tools, and content signals.
• Report generation with per-skill tables, inferred effort, priority fixes, and a copy-paste-ready patch block for missing or mismatched effort fields.
• Use Cases: onboarding a new project, pre-commit quality checks, bulk-import verification, and adding effort metadata to an existing skill library.

Quick Start

Run an audit of all SKILL.md files in this repository and output a scored report with recommended effort fields.