skills-eval

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Evaluate Claude skill quality through auditing. Use when reviewing or auditing skills.

AI & Automation 323 stars 29 forks Updated today MIT

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Skill Content

# Skills Evaluation and Improvement ## When NOT To Use - Writing a new skill (use `abstract:skill-authoring`) - Evaluating hooks (use `abstract:hooks-eval`) - Evaluating rules (use `abstract:rules-eval`) ## Table of Contents 1. [Overview](#overview) 2. [Quick Start](#quick-start) 3. [Evaluation Workflow](#evaluation-workflow) 4. [Evaluation and Optimization](#evaluation-and-optimization) 5. [Resources](#resources) ## Overview This framework audits Claude skills against quality standards to improve performance and reduce token consumption. Automated tools analyze skill structure, measure context usage, and identify specific technical improvements. Run verification commands after each audit to confirm fixes work correctly. The `skills-auditor` provides structural analysis, while the `improvement-suggester` ranks fixes by impact. Compliance is verified through the `compliance-checker`. Runtime efficiency is monitored by `tool-performance-analyzer` and `token-usage-tracker`. ## Quick Start ### Basic Audit Run a full audit of all skills or target a specific file to identify structural issues. ```bash # Audit all skills make audit-all # Audit specific skill make audit-skill TARGET=path/to/skill/SKILL.md ``` ### Analysis and Optimization Use `skill_analyzer.py` for complexity checks and `token_estimator.py` to verify the context budget. ```bash make analyze-skill TARGET=path/to/skill/SKILL.md make estimate-tokens TARGET=path/to/skill/SKILL.md ``` ### Improvements Generat...

Details

Author
athola
Repository
athola/claude-night-market
Created
8 months ago
Last Updated
today
Language
Python
License
MIT

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