Create specialized agent workflows that coordinate multiple AI agents to tackle complex engineering tasks. Instead of a single agent trying to handle everything, you can orchestrate teams of focused specialists that work together.

1. Edit an existing agent: Start with my-custom-agent.ts and modify it for your needs
2. Test your agent: Run codebuff --agent your-agent-name
3. Publish your agent: Run codebuff publish your-agent-name

• For detailed documentation, see agent-guide.md.
• For examples, check the examples/ directory.
• Join our Discord community and ask your questions!

Modern software projects are complex ecosystems with thousands of files, multiple frameworks, intricate dependencies, and domain-specific requirements. A single AI agent trying to understand and modify such systems faces fundamental limitations—not just in knowledge, but in the sheer volume of information it can process at once.

Agent workflows elegantly solve this by breaking large tasks into focused sub-problems. When working with large codebases (100k+ lines), each specialist agent receives only the narrow context it needs—a security agent sees only auth code, not UI components—keeping the context for each agent manageable while ensuring comprehensive coverage.

This is about efficient AI context management, not recreating a human department. Simply creating a "frontend-developer" agent misses the point. AI agents don't have human constraints like context-switching or meetings. Their power comes from hyper-specialization, allowing them to process a narrow domain more deeply than a human could, then coordinating seamlessly with other specialists.

Here's an example of a git-committer agent that creates good commit messages:

export default {
  id: 'git-committer',
  displayName: 'Git Committer',
  model: 'openai/gpt-5-nano',
  toolNames: ['read_files', 'run_terminal_command', 'end_turn'],

  instructionsPrompt:
    'You create meaningful git commits by analyzing changes, reading relevant files for context, and crafting clear commit messages that explain the "why" behind changes.',

  async *handleSteps() {
    // Analyze what changed
    yield { tool: 'run_terminal_command', command: 'git diff' }
    yield { tool: 'run_terminal_command', command: 'git log --oneline -5' }

    // Stage files and create commit with good message
    yield 'STEP_ALL'
  },
}

This agent systematically analyzes changes, reads relevant files for context, then creates commits with clear, meaningful messages that explain the "why" behind changes.