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Name: skill-tester Tier: POWERFUL Category: Engineering Quality Assurance Dependencies: None (Python Standard Library Only) Author: Claude Skills Engineering Team Version: 1.0.0 Last Updated: 2026-02-16.
zh_description
用于技能、tester，支持开发、调试、评审和交付。
version
1.0.0
author
seaworld008
source
in-house
source_url
tags
["development", "skill", "tester"]
created_at
2026-03-04
updated_at
2026-03-20
quality
5
complexity
intermediate
Skill Tester
Name: skill-tester
Tier: POWERFUL
Category: Engineering Quality Assurance
Dependencies: None (Python Standard Library Only)
Author: Claude Skills Engineering Team
Version: 1.0.0
Last Updated: 2026-02-16
Description
The Skill Tester is a comprehensive meta-skill designed to validate, test, and score the quality of skills within the claude-skills ecosystem. This powerful quality assurance tool ensures that all skills meet the rigorous standards required for BASIC, STANDARD, and POWERFUL tier classifications through automated validation, testing, and scoring mechanisms.
As the gatekeeping system for skill quality, this meta-skill provides three core capabilities:
Structure Validation - Ensures skills conform to required directory structures, file formats, and documentation standards
Script Testing - Validates Python scripts for syntax, imports, functionality, and output format compliance
Quality Scoring - Provides comprehensive quality assessment across multiple dimensions with letter grades and improvement recommendations
This skill is essential for maintaining ecosystem consistency, enabling automated CI/CD integration, and supporting both manual and automated quality assurance workflows. It serves as the foundation for pre-commit hooks, pull request validation, and continuous integration processes that maintain the high-quality standards of the claude-skills repository.
Resource Management: Automatic cleanup of temporary files and subprocess resources
Configuration Flexibility: Configurable timeouts, memory limits, and validation strictness
Security & Safety
Safe Execution Environment
Sandboxed Testing: Scripts execute in controlled environment with timeout protection
Resource Limits: Memory and CPU usage monitoring to prevent resource exhaustion
Input Validation: All inputs sanitized and validated before processing
No Network Access: Offline operation ensures no external dependencies or network calls
Security Best Practices
No Code Injection: Static analysis only, no dynamic code generation
Path Traversal Protection: Secure file system access with path validation
Minimal Privileges: Operates with minimal required file system permissions
Audit Logging: Comprehensive logging for security monitoring and troubleshooting
Troubleshooting & Support
Common Issues & Solutions
Validation Failures
Missing Files: Check directory structure against tier requirements
Import Errors: Ensure only standard library imports are used
Documentation Issues: Verify SKILL.md frontmatter and section completeness
Script Testing Problems
Timeout Errors: Increase timeout limit or optimize script performance
Execution Failures: Check script syntax and import statement validity
Output Format Issues: Ensure proper JSON formatting and dual output support
Quality Scoring Discrepancies
Low Scores: Review scoring rubric and improvement recommendations
Tier Misclassification: Verify skill complexity against tier requirements
Inconsistent Results: Check for recent changes in quality standards or scoring weights
Debugging Support
Verbose Mode: Detailed logging and execution tracing available
Dry Run Mode: Validation without execution for debugging purposes
Debug Output: Comprehensive error reporting with file locations and suggestions
Future Enhancements
Planned Features
Machine Learning Quality Prediction: AI-powered quality assessment using historical data
Performance Benchmarking: Execution time and resource usage tracking across skills
Dependency Analysis: Automated detection and validation of skill interdependencies
Quality Trend Analysis: Historical quality tracking and regression detection
Integration Roadmap
IDE Plugins: Real-time validation in popular development environments
Web Dashboard: Centralized quality monitoring and reporting interface
API Endpoints: RESTful API for external integration and automation
Notification Systems: Automated alerts for quality degradation or validation failures
Conclusion
The Skill Tester represents a critical infrastructure component for maintaining the high-quality standards of the claude-skills ecosystem. By providing comprehensive validation, testing, and scoring capabilities, it ensures that all skills meet or exceed the rigorous requirements for their respective tiers.
This meta-skill not only serves as a quality gate but also as a development tool that guides skill authors toward best practices and helps maintain consistency across the entire repository. Through its integration capabilities and comprehensive reporting, it enables both manual and automated quality assurance workflows that scale with the growing claude-skills ecosystem.
The combination of structural validation, runtime testing, and multi-dimensional quality scoring provides unparalleled visibility into skill quality while maintaining the flexibility needed for diverse skill types and complexity levels. As the claude-skills repository continues to grow, the Skill Tester will remain the cornerstone of quality assurance and ecosystem integrity.
