Implement Intelligent Caching for AI Analysis Results

[AndreaGriffiths11]

Description

Implement intelligent caching for AI analysis results to reduce API calls, improve performance, and provide faster subsequent analyses.

Acceptance Criteria

• Cache AI analysis results in VS Code workspace state
• Implement configurable TTL (time-to-live) for cache entries
• Add cache invalidation when repository changes are detected
• Add user setting for cache duration (default: 24 hours)
• Show cache status in UI (cached vs fresh analysis)
• Add "Clear Cache" command

Technical Notes

• Use context.workspaceState for persistent caching
• Hash repository data to create cache keys
• Implement LRU eviction for memory management
• Follow existing patterns in expertise-analyzer.ts

Configuration

{
  "teamxray.cache.enabled": true,
  "teamxray.cache.ttlHours": 24
}

Files to Modify/Create

• src/core/expertise-analyzer.ts - Add caching logic
• src/utils/cache-manager.ts (new) - Cache utility class
• package.json - Add configuration contributions

Demo Value

Showcases Copilot coding agent's ability to:

• Implement performance optimizations
• Work with VS Code storage APIs
• Add user-configurable settings
• Create new utility classes