mcpField
A
auto-claude

auto-claude

github.com/travisjneumanAgent workflows106131 installsUpdated 1d ago
Repository

About auto-claude

Auto-Claude is a multi-agent coding skill for implementing defined, multi-file features in established codebases. It analyzes the project, plans the work, implements in an isolated Git worktree, and runs iterative QA before review.

Key features

  1. 01Codebase analysis and semantic baseline
  2. 02Implementation specification generation
  3. 03Coordinated autonomous agents
  4. 04Isolated Git worktree development
  5. 05Iterative QA validation
  6. 06Graphiti-powered context memory

Use cases

  1. 01Adding authentication or API features
  2. 02Implementing forms and CRUD tasks
  3. 03Refining features through QA cycles

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/travisjneuman/.claude --skill auto-claude

After installing, type/auto-claudein Claude Code to confirm it loaded.

Details

From the project README

Auto-Claude: Autonomous Coding Framework

Autonomous multi-agent system for complex feature implementation with QA validation.

When to Use

✅ Use Auto-Claude for:

  • Complexity 3-4 - Well-defined features, multiple files
  • Established codebases with clear patterns
  • Repetitive tasks (CRUD, forms, API endpoints, auth flows)
  • When you prefer review-at-end vs step-by-step
  • Features requiring iterative refinement with QA validation

❌ Don't use Auto-Claude for:

  • Complexity 1-2 - Use manual /start-task instead
  • Complexity 5+ - Use /gsd:new-project instead
  • Greenfield projects (no existing codebase patterns)
  • Exploratory/research tasks (unclear requirements)
  • Simple typo fixes or config changes
  • Tasks requiring human decision-making during implementation

Quick Guide:

  • Complexity 1-2 → Manual implementation
  • Complexity 3-4 → Auto-Claude (autonomous)
  • Complexity 5+ → GSD (multi-phase)

Core Capabilities

  1. Codebase Analysis - Generates semantic baseline
  2. Spec Generation - Creates detailed implementation plan
  3. Autonomous Implementation - Multi-agent coordination
  4. Git Worktree Isolation - Safe development in separate worktree
  5. QA Validation - Iterative quality checks
  6. Memory System - Graphiti-powered context retention

Workflow

# From project directory:
/auto-claude Add user authentication with JWT tokens

What Happens:

  1. Analyzes project structure → generates baseline
  2. Creates implementation spec → stores in ~/.auto-claude/specs/
  3. Creates git worktree → isolated development environment
  4. Autonomous agents implement → with QA loops
  5. Returns completed code → ready for review

Output Location: ~/.auto-claude/ (gitignored)

Integration with Existing Workflows

Manual Implementation:

/start-task [description]  → Claude implements step-by-step

Autonomous Implementation:

/auto-claude [description] → Auto-Claude implements autonomously

Multi-Phase Projects:

/gsd:new-project          → GSD for project management

Configuration

Location: ~/.auto-claude/.env

Required:

  • CLAUDE_CODE_OAUTH_TOKEN - Get from /settings in Claude Code

Optional (Recommended):

  • GRAPHITI_ENABLED=true - Semantic memory
  • GOOGLE_API_KEY - For Gemini embeddings (memory feature)
  • Alternative: Ollama (local) or disable memory

Trade-offs

Strengths:

  • Autonomous with minimal oversight
  • QA validation ensures quality
  • Git worktree prevents main branch disruption
  • Memory learns from previous sessions

Limitations:

  • Best for established codebases
  • Requires clear specifications
  • Uses tokens for multi-agent iterations
  • Manual merge required after completion

Examples

Good use cases:

  • "Add user authentication with JWT tokens and session management"
  • "Implement dark mode toggle with localStorage persistence"
  • "Refactor API layer to use async/await instead of callbacks"
  • "Add pagination to user list with 20 items per page"
  • "Create export-to-CSV functionality for reports"

Poor use cases:

  • "Fix typo in README" (too simple)
  • "Explore best approach for state management" (exploratory)
  • "Build entire e-commerce platform" (too large, use GSD)
  • "Make the app better" (too vague)

Typical Timeline

  • Analysis: 30 seconds
  • Spec Generation: 1-2 minutes
  • Implementation: 5-15 minutes (depends on complexity)
  • QA Validation: 2-5 minutes
  • Your Review: 5-10 minutes

Total: 15-30 minutes for most features

Related

  • generic-feature-developer - Manual implementation patterns
  • debug-systematic - Systematic debugging
  • test-specialist - Testing strategies

Documentation

See ~/.claude/docs/AUTO-CLAUDE-GUIDE.md for:

  • Complete setup instructions
  • Real-world examples with detailed walkthroughs
  • Troubleshooting guide
  • Performance tips
  • Comparison with other workflows

Comments

Markdown supported