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3 changes: 3 additions & 0 deletions .gitignore
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# Work in progress packages (not ready for commit)
packages/benchmark/

# Benchmark studies and session logs
studies/
48 changes: 47 additions & 1 deletion PLAN.md
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---

## Current: Extended Git Intelligence (v0.5.0)
## Current: Quality & Thoroughness (v0.4.x)

> Addressing gaps identified in benchmark study comparing dev-agent vs baseline Claude Code.

**Context:** Benchmarks showed dev-agent provides 44% cost savings and 19% faster responses, but with quality trade-offs. These improvements close the gap.

### Benchmark-Driven Improvements

| Task | Gap Identified | Priority | Status |
|------|----------------|----------|--------|
| Diagnostic command suggestions | Baseline provided shell commands for debugging; dev-agent didn't | 🔴 High | 🔲 Todo |
| Test file inclusion hints | Baseline read test files; dev-agent skipped them | 🔴 High | 🔲 Todo |
| Code example extraction | Baseline included more code snippets in responses | 🟡 Medium | 🔲 Todo |
| Exhaustive mode for debugging | Option for thorough exploration vs fast satisficing | 🟡 Medium | 🔲 Todo |
| Related files suggestions | "You might also want to check: X, Y, Z" | 🟡 Medium | 🔲 Todo |

### Tool Description Refinements (Done in v0.4.2)

| Task | Status |
|------|--------|
| Improved dev_search description ("USE THIS FIRST") | ✅ Done |
| Improved dev_map description (vs list_dir) | ✅ Done |
| Improved dev_explore description (workflow hints) | ✅ Done |
| Improved dev_refs description (specific symbols) | ✅ Done |
| All 9 adapters registered in CLI | ✅ Done |

---

## Next: Extended Git Intelligence (v0.5.0)

> Building on git history with deeper insights.

Expand Down Expand Up @@ -286,6 +314,24 @@ How we know dev-agent is working:
4. **Daily use:** We actually use it ourselves (dogfooding)
5. **LLM effectiveness:** Claude/Cursor make better suggestions with dev-agent

### Benchmark Results (v0.4.2)

Measured against baseline Claude Code across 5 task types:

| Metric | Baseline | With dev-agent | Improvement |
|--------|----------|----------------|-------------|
| Cost per session | $1.82 | $1.02 | **-44%** |
| Time per session | 14.1 min | 11.5 min | **-19%** |
| Tool calls | 69 | 40 | **-42%** |
| Files examined | 23 | 15 | **-35%** |

**Trade-offs identified:**
- Less thorough for debugging (missing diagnostic commands)
- Fewer code examples in responses
- Skips test files (baseline reads them)

**Target users:** Mid-to-senior engineers who value speed over exhaustiveness for routine exploration tasks.

---

## Contributing
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[![pnpm](https://img.shields.io/badge/pnpm-8.15.4-orange.svg)](https://pnpm.io/)
[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](LICENSE)

**Local-first repository context provider for AI tools. Semantic code search, git history, relationship queries, and codebase mapping via MCP.**
**Local semantic code search for Cursor and Claude Code via MCP.**

## What is dev-agent?
## What it does

dev-agent provides **rich, structured context** to AI assistants like Claude and Cursor. Instead of AI tools reading files one at a time, dev-agent gives them:
dev-agent indexes your codebase and provides 9 MCP tools to AI assistants. Instead of AI tools grepping through files, they can ask conceptual questions like "where do we handle authentication?"

- 🔍 **Semantic search** with code snippets and relationships
- 🗺️ **Codebase maps** showing structure and change frequency
- 🔗 **Relationship queries** (what calls what)
- 📜 **Git history search** (who changed what and why)
- 📋 **Issue context** assembled for planning
- `dev_search` — Semantic code search by meaning
- `dev_refs` — Find callers/callees of functions
- `dev_map` — Codebase structure with change frequency
- `dev_history` — Semantic search over git commits
- `dev_plan` — Assemble context for GitHub issues
- `dev_explore` — Find similar code, trace relationships
- `dev_gh` — Search GitHub issues/PRs semantically
- `dev_status` / `dev_health` — Monitoring

**Philosophy:** Provide data, let LLMs reason. We don't try to be smart with heuristics—we provide comprehensive context so AI assistants can be smart.
## Measured results

We benchmarked dev-agent against baseline Claude Code across 5 task types:

| Metric | Baseline | With dev-agent | Change |
|--------|----------|----------------|--------|
| Cost | $1.82 | $1.02 | **-44%** |
| Time | 14.1 min | 11.5 min | **-19%** |
| Tool calls | 69 | 40 | **-42%** |

**Trade-offs:** Faster but sometimes less thorough. Best for implementation tasks and codebase exploration. For deep debugging, baseline Claude may read more files.

## When to use it

**Good fit:**
- Large or unfamiliar codebases
- Implementation tasks ("add a feature like X")
- Exploring how code works
- Reducing AI API costs

**Less useful:**
- Small codebases you already know well
- Deep debugging sessions
- When thoroughness matters more than speed

## Quick Start

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# Introduction

**dev-agent** is a local-first repository context provider for AI tools. It gives AI assistants like Cursor and Claude Code deep understanding of your codebase through semantic search, code analysis, and GitHub integration.
**dev-agent** provides semantic code search to AI assistants like Cursor and Claude Code via MCP.

## The Problem
We built this for ourselves. When exploring large codebases, we found AI tools spending too much time grepping through files. dev-agent gives them a faster path: search by meaning, not keywords.

AI coding assistants are powerful, but they struggle with context:
## What it does

- They can't search your codebase semantically
- They don't understand relationships between files
- They lack awareness of your GitHub issues and PRs
- They hallucinate about code that doesn't exist
1. **Indexes your codebase** locally with embeddings (all-MiniLM-L6-v2)
2. **Exposes 9 MCP tools** for semantic search, code relationships, git history
3. **Integrates with GitHub** to search issues and PRs semantically

## The Solution
## Measured impact

dev-agent solves this by:
We benchmarked dev-agent against baseline Claude Code:

1. **Indexing your codebase** with local embeddings (all-MiniLM-L6-v2)
2. **Exposing semantic search** via the Model Context Protocol (MCP)
3. **Integrating with GitHub** to understand your project's history
4. **Providing specialized tools** for planning, exploration, and more
| Metric | Baseline | With dev-agent | Change |
|--------|----------|----------------|--------|
| Cost | $1.82 | $1.02 | **-44%** |
| Time | 14.1 min | 11.5 min | **-19%** |
| Tool calls | 69 | 40 | **-42%** |

**Trade-off:** Faster but sometimes less thorough. Best for implementation tasks and exploration. For deep debugging, baseline Claude may read more files.

## Key Features

| Feature | Description |
|---------|-------------|
| **Semantic Search** | Find code by meaning, not keywords |
| **AST Analysis** | Type-aware understanding of your code |
| **Relationship Queries** | What calls this function? What does it call? |
| **Git History** | Semantic search over commits |
| **GitHub Integration** | Search issues and PRs semantically |
| **Local-First** | Your code never leaves your machine |
| **MCP Native** | Works with Cursor, Claude Code, VS Code |
| **100% Local** | Your code never leaves your machine |

## Architecture Overview
## Architecture

dev-agent is built as a monorepo with specialized packages:
dev-agent is a monorepo:

- **@lytics/dev-agent-core** — Repository scanning, vector storage, GitHub integration
- **@lytics/dev-agent-core** — Scanning, vector storage, GitHub integration
- **@lytics/dev-agent-cli** — Command-line interface
- **@lytics/dev-agent-mcp** — MCP server with tool adapters
- **@lytics/dev-agent-subagents** — Specialized agents (planner, explorer, PR manager)
- **@lytics/dev-agent-mcp** — MCP server with 9 tool adapters
- **@lytics/dev-agent-subagents** — Planner, explorer agents

## Next Steps

- [Installation →](/docs/install) — Get dev-agent installed in under 2 minutes
- [Quickstart →](/docs/quickstart) — From zero to semantic search in 5 minutes
- [Quickstart →](/docs/quickstart) — Index and search in 5 minutes

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