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Agent Booster: Complete Planning Documentation

Ultra-fast code application engine - 200x faster than Morph LLM at $0 cost

📚 Documentation Index

Core Planning Documents

  1. 00-OVERVIEW.md - Vision, Objectives & Success Metrics

    • Project vision and motivation
    • Core objectives (performance, accuracy, cost, DX)
    • Key features and capabilities
    • Development phases (10 weeks)
    • Success criteria and metrics
    • Open questions and next steps

  2. 01-ARCHITECTURE.md - Technical Architecture & Design

    • System architecture diagrams
    • Rust crate structure (core, native, wasm)
    • Module breakdown (parser, embeddings, vector, merge)
    • Data flow and algorithms
    • Performance optimizations
    • Testing strategy
    • Error handling

  3. 02-INTEGRATION.md - Integration with Agentic-Flow & MCP

    • Agentic-flow integration (.env, tools, CLI)
    • MCP server architecture
    • Tool implementations
    • Configuration presets
    • Metrics & monitoring
    • Workspace detection

  4. 03-BENCHMARKS.md - Benchmark Methodology

    • Test dataset design (100 samples)
    • Morph LLM baseline (Claude Sonnet/Opus/Haiku)
    • Agent Booster variants (native/WASM/TypeScript)
    • Metrics collection (performance, accuracy, cost)
    • Statistical analysis
    • Expected results (166x speedup, 100% cost savings)

  5. 04-NPM-SDK.md - NPM SDK & CLI Design

    • Package structure (agent-booster, agent-booster-cli)
    • Auto-detection loader (native > WASM)
    • TypeScript definitions
    • CLI commands (apply, batch, watch, mcp, dashboard)
    • Platform-specific packages
    • Distribution strategy

  6. README.md - Main README (for crate/package)

    • Quick start guide
    • Performance comparison tables
    • Feature comparison vs Morph LLM
    • Usage examples
    • Installation instructions
    • Documentation links

  7. GITHUB-ISSUE.md - GitHub Issue Template

    • Complete feature request
    • Implementation roadmap (10 weeks)
    • Task breakdown by phase
    • Success criteria
    • Testing checklist
    • Release plan

🎯 Quick Reference

Key Performance Targets

Metric Morph LLM Agent Booster Improvement
Latency (p50) 6,000ms 30ms 200x faster ⚡
Throughput 10,500 tok/s 1M+ tok/s 95x faster ⚡
Cost/edit $0.01 $0.00 100% savings 💰
Accuracy 98% 97-99% Comparable ✅
Privacy API Local 100% private 🔒

Technology Stack

Core:
├── Rust (performance + safety)
├── Tree-sitter (AST parsing, 40+ languages)
├── ONNX Runtime (local ML inference)
└── HNSW (vector similarity)

Bindings:
├── napi-rs (Node.js native addon)
├── wasm-bindgen (WebAssembly)
└── TypeScript (type-safe API)

Models:
├── jina-embeddings-v2-base-code (768-dim, best)
└── all-MiniLM-L6-v2 (384-dim, fast)

Project Structure

agent-booster/
├── crates/
│   ├── agent-booster/           # Core Rust library
│   ├── agent-booster-native/    # napi-rs bindings
│   └── agent-booster-wasm/      # WASM bindings
│
├── npm/
│   ├── agent-booster/           # Main NPM package
│   └── agent-booster-cli/       # Standalone CLI
│
├── benchmarks/                   # Benchmark suite
│   ├── datasets/                # Test code samples
│   ├── baselines/               # Morph LLM baselines
│   └── results/                 # Benchmark outputs
│
└── docs/                        # Documentation

10-Week Implementation Roadmap

  • Week 1-2: Foundation (Rust setup, tree-sitter, benchmarks)
  • Week 3-4: Core engine (embeddings, vector search, merge)
  • Week 5: Native integration (napi-rs, NPM package)
  • Week 6: WASM support (browser compatibility)
  • Week 7: Agentic-flow integration (.env, tools)
  • Week 8: MCP server (Claude/Cursor/VS Code)
  • Week 9: CLI & SDK (npx agent-booster)
  • Week 10: Documentation & release

🚀 Getting Started

For Reviewers

  1. Read 00-OVERVIEW.md for high-level vision
  2. Review 01-ARCHITECTURE.md for technical design
  3. Check 03-BENCHMARKS.md for validation plan
  4. See GITHUB-ISSUE.md for complete task breakdown

For Implementers

  1. Start with 01-ARCHITECTURE.md for crate structure
  2. Follow GITHUB-ISSUE.md roadmap (week by week)
  3. Reference 02-INTEGRATION.md for agentic-flow integration
  4. Use 04-NPM-SDK.md for NPM package design

For Users

  1. Start with README.md for quick start
  2. Check 02-INTEGRATION.md for usage examples
  3. Review 03-BENCHMARKS.md for performance data

📊 Expected Results

Performance (100 edits)

Morph LLM baseline:
├─ Total time: 10 minutes
├─ Total cost: $1.00
└─ Method: API calls

Agent Booster:
├─ Total time: 3.5 seconds    ⚡ 170x faster
├─ Total cost: $0.00           💰 100% savings
└─ Method: Local inference

Hybrid (80% Agent Booster, 20% fallback):
├─ Total time: 1.4 minutes    ⚡ 7x faster
├─ Total cost: $0.20          💰 80% savings
└─ Best accuracy + speed

Accuracy

Complexity Morph LLM Agent Booster Difference
Simple 99.2% 98.5% -0.7%
Medium 97.8% 96.2% -1.6%
Complex 96.1% 93.8% -2.3%
Overall 98.0% 96.8% -1.2%

🎯 Success Metrics

MVP (v0.1)

  • Complete planning
  • Core Rust library functional
  • 100x speedup demonstrated
  • 95%+ accuracy on simple edits
  • Agentic-flow integration working

Production (v1.0)

  • WASM support
  • MCP server
  • 5+ languages
  • >80% test coverage
  • Documentation site

Adoption

  • 100+ GitHub stars
  • 1,000+ npm downloads
  • 10+ production users
  • 5+ contributors

💡 Key Innovations

  1. Vector-Based Semantic Merging - No LLM needed for code application
  2. Hybrid Fallback Strategy - Best of both worlds (speed + accuracy)
  3. Universal Deployment - Native, WASM, MCP server from one codebase
  4. Zero Runtime Cost - 100% local after model download
  5. Deterministic Results - Same input always produces same output

🤝 Next Steps

  1. Review Planning - Get team feedback on architecture
  2. Finalize Scope - Confirm MVP features
  3. Create GitHub Issue - Use GITHUB-ISSUE.md template
  4. Begin Phase 1 - Setup Rust workspace and benchmarks
  5. Recruit Contributors - Find Rust developers interested

📝 Questions or Feedback?

  • Open an issue on GitHub
  • Comment on the planning documents
  • Join the discussion in Discord
  • DM the project maintainers

Ready to make AI code editing 200x faster! 🚀

Last updated: 2025-10-07