Audits and optimizes Claude skills to improve performance, ensure compliance, and reduce token consumption.
The Claude Skill Quality Evaluator is a specialized framework designed to audit and refine custom Claude skills against production-grade standards. It provides a suite of automated tools that analyze skill structures, measure context usage, and identify specific technical improvements. By utilizing features like the token-usage-tracker and compliance-checker, developers can ensure their skills are efficient, follow modular design patterns, and are fully compatible with the Claude SDK before deployment. It is the definitive tool for maintaining high-quality, high-performance AI capabilities.
Key Features
01Automated structural auditing of skill definitions
020 GitHub stars
03Prioritized improvement suggestions based on impact analysis
04Performance benchmarking for tool-use and runtime efficiency
05Detailed token usage tracking and context budget estimation
06Compliance checking against modular design and SDK standards
Use Cases
01Optimizing token efficiency to reduce operational costs and improve model response latency
02Auditing existing skills to identify and fix structural flaws before production deployment
03Validating skill compliance with specific architectural patterns and SDK requirements
