What It Does — Orchestrating Parallel Claude Code Agents
RepoWire is an open-source orchestrator that connects multiple Claude Code sessions into a coordinated network. Instead of running one Claude Code agent sequentially through tasks, RepoWire spawns specialized agents that work in parallel — similar to the "swarm mode" concept from the SKILL.md methodology, but applied across your entire development workflow.
When you give RepoWire a complex task (like "refactor this entire codebase" or "add comprehensive testing"), it breaks the work into specialized subtasks and assigns them to different Claude Code agents running simultaneously. One agent might handle API layer refactoring while another works on database migrations, while a third writes tests — all at the same time.
Setup — Simple Configuration for Parallel Processing
Installation is straightforward:

# Clone the repository
git clone https://github.com/prassanna-ravishankar/repowire
cd repowire
# Install dependencies
npm install
# Configure your Claude Code instances
cp config.example.json config.json
Edit config.json to specify how many Claude Code agents you want running and their specializations:
{
"agents": [
{
"name": "architect",
"role": "Handles system design and major refactoring",
"max_tokens": 8000
},
{
"name": "tester",
"role": "Writes and runs comprehensive test suites",
"max_tokens": 4000
},
{
"name": "documenter",
"role": "Generates documentation and code comments",
"max_tokens": 3000
}
],
"orchestrator": {
"task_timeout": 300,
"max_parallel_tasks": 3
}
}
Start the network:
# Launch all configured agents
node start-network.js
# Or run a specific workflow
node run-workflow.js --task="refactor-and-test" --project="./my-app"
When To Use It — Specific Multi-Agent Scenarios
1. Large-Scale Refactoring
Instead of having Claude Code work through thousands of lines sequentially, use RepoWire to split the work:
- Agent 1: Analyzes current architecture and creates migration plan
- Agent 2: Refactors core business logic
- Agent 3: Updates all test files to match new interfaces
All three work simultaneously, cutting refactoring time by 60-70%.
2. Comprehensive Testing Generation
Building on the SKILL.md methodology, RepoWire can spawn multiple testing agents:
- Happy Path Agent: Generates core user flow tests
- Edge Case Agent: Creates tests for boundary conditions and error states
- Performance Agent: Writes load and stress tests
Each agent writes to its own test directory, then RepoWire merges and deduplicates the results.
3. Documentation Overhaul
When you need to document an entire codebase:
- API Doc Agent: Documents all endpoints and interfaces
- Code Comment Agent: Adds inline documentation to complex functions
- README Agent: Creates comprehensive project documentation
4. Security Audit
Run multiple specialized security agents:
- Dependency Scanner: Checks for vulnerable packages
- Code Analyzer: Looks for security anti-patterns
- Configuration Reviewer: Audits environment and deployment configs
Integration with CLAUDE.md for Consistent Behavior
RepoWire works best when each agent has its own CLAUDE.md file tailored to its specialization. Create a .claude/agents/ directory:
.claude/
├── agents/
│ ├── architect.CLAUDE.md
│ ├── tester.CLAUDE.md
│ └── documenter.CLAUDE.md
└── settings.json
Each specialized CLAUDE.md contains role-specific instructions. For example, tester.CLAUDE.md might include:
# Tester Agent Configuration
## Testing Philosophy
- Write tests that fail when behavior changes, not when implementation changes
- Prioritize integration tests over unit tests for business logic
- Use the same locator priority as SKILL.md: getByRole > getByLabel > getByText

## Project-Specific Rules
- All tests go in `/tests/` directory
- Use Jest for unit tests, Playwright for E2E
- Mock external APIs with MSW
## Output Format
- Save test files with `.test.js` extension
- Include descriptive test names
- Add comments for complex test scenarios
RepoWire automatically loads the appropriate CLAUDE.md for each agent based on its role.
Cost Management with Parallel Processing
Running multiple agents simultaneously increases token usage, but RepoWire includes optimization features:

- Token Budgeting: Set per-agent and total session limits
- Result Caching: Agents share findings to avoid duplicate analysis
- Progressive Disclosure: Agents only receive relevant code sections
Configure budgets in your workflow:
// In your workflow configuration
{
"token_management": {
"total_budget": 50000,
"per_agent_budget": 20000,
"emergency_stop": true
}
}
Real-World Example: Full Stack Feature Development
Here's how RepoWire handles adding a new feature to a web application:
# Command to orchestrate feature development
node run-workflow.js \
--workflow="full-stack-feature" \
--feature="user-notification-system" \
--project="./app" \
--agents=4
RepoWire then:
- Agent 1 (Backend): Creates database schema and API endpoints
- Agent 2 (Frontend): Builds UI components and state management
- Agent 3 (Testing): Writes tests for both frontend and backend
- Agent 4 (Documentation): Updates API docs and creates user guide
All agents work in parallel, sharing progress through RepoWire's coordination layer. When conflicts arise (like two agents trying to modify the same file), RepoWire pauses execution and requests human intervention.
Getting Started with Minimal Configuration
Start small with a two-agent setup:
// minimal-config.json
{
"agents": [
{
"name": "coder",
"role": "Write and modify application code"
},
{
"name": "reviewer",
"role": "Review code for bugs and improvements"
}
]
}
Run it with:
node start-network.js --config="minimal-config.json"
Then give it a simple task to see the parallel processing in action:
# In the RepoWire interface
> refactor utils/ directory to use ES6 modules
The coder agent will handle the refactoring while the reviewer agent simultaneously checks each file as it's modified.
Limitations and Considerations
- Resource Intensive: Each agent runs a separate Claude Code instance
- Coordination Overhead: Complex tasks require careful agent role definition
- Cost Multiplication: Token usage scales with agent count
- Debugging Complexity: Issues can arise from agent interactions
Start with 2-3 agents for specific, well-defined tasks before scaling to larger networks.
RepoWire represents the next evolution of Claude Code workflows — moving from sequential AI assistance to parallel, specialized agent networks that can tackle complex development tasks in a fraction of the time.





