[Feature Request] Skill Governance: Discovery, versioning, compatibility checks, and quality metrics

[cc3wangdehai-hue]

Problem

The current Skill system lacks mature governance mechanisms:

1. Discovery is difficult: Users struggle to find suitable Skills among hundreds
2. Version chaos: Skill versions are inconsistent, updates have no notification
3. Compatibility issues: No clear prompt when a Skill is incompatible with the platform version
4. Quality variance: No quality assessment mechanism for Skills
5. No dependency management: Skills cannot declare dependencies on other Skills

Proposed Solution

1. Skill Marketplace

• Unified discovery with search, categories, and tags
• Quality scoring: download count, user ratings, update frequency
• Featured/recommended Skills based on usage patterns

2. Semantic Versioning

• All Skills follow semver (MAJOR.MINOR.PATCH)
• Auto-update checking with changelog display
• Breaking change detection and migration guides

3. Compatibility Checks

• Pre-install validation against platform version
• Runtime compatibility assertions
• Graceful degradation when dependencies are missing

4. Quality Indicators

• Trust score: Based on author reputation, review history, test coverage
• Health score: Update recency, issue response time, dependency freshness
• Usage metrics: Active installations, success rate, average cost per use

5. Dependency Management

• Skill manifest declares dependencies (like package.json)
• Automatic dependency resolution at install time
• Conflict detection and resolution suggestions

Impact

• Healthier Skill ecosystem with clear quality signals
• Fewer user pain points from broken/incompatible Skills
• High-quality Skills get deserved visibility
• Easier onboarding for new users

Priority

P2 (Medium) - Ecosystem health improvement