# Progressive Context Management Documentation (v0.3.2)
This directory contains all documentation related to the Progressive Context Management feature released in v0.3.2.
## Overview
Progressive Context Management delivers 50-70% token reduction for initial queries by implementing a multi-level context API that provides file → class → method hierarchy with semantic caching.
## Documentation Files
### Usage Documentation
- **[Progressive Search Usage Guide](./progressive-search-usage-guide.md)** 📚 - **START HERE** - Complete guide on using progressive search
- **[Implementation Status](./IMPLEMENTATION_STATUS.md)** ✅ - Current implementation status and what's been delivered
### Technical Documentation
- **[Implementation Plan](./progressive-context-implementation-plan.md)** - Original implementation roadmap
- **[Integration Strategy](./progressive-context-integration-strategy.md)** - Integration approach with existing tools
- **[Code Structure](./progressive-context-code-structure.md)** - Code organization and architecture
## Key Features
- **50-70% token reduction** for high-level queries
- **Multi-level context API**: file → class → method hierarchy
- **Semantic caching** for query similarity matching
- **Query intent classification** for automatic level selection
- **Progressive expansion** allowing drill-down into details
- **Backward compatible** with existing search tools
## Integration Approach
Rather than creating new MCP tools, we'll enhance existing ones:
- `search()` - General search with progressive context
- `search_code()` - Code search with hierarchy support
- `search_docs()` - Documentation search with section levels
New parameters:
- `context_level`: "auto", "file", "class", "method", "full"
- `progressive_mode`: Enable/disable progressive features
- `include_expansion_options`: Show drill-down options
- `semantic_cache`: Use similarity-based caching
## Timeline
- **Days 1-3**: Core infrastructure
- **Days 4-6**: Semantic caching
- **Days 7-8**: Query intelligence
- **Days 9-10**: Integration & testing
Total: ~1.5 weeks
## Success Metrics
- 50-70% token reduction for high-level queries
- 40% cache hit rate
- 80% feature adoption
- No degradation in search quality
