CLI tool for running AI coding agents in a loop using the Ralph Wiggum methodology.
Chief uses Claude Code to plan and execute tasks in your current repository, tracking plans and task files under .chief/.
- Bun runtime
- Claude Code CLI installed and authenticated
- GitHub CLI (
gh) for PR creation - Git
# Clone the repository
git clone git@github.com:mauricekleine/chief.git chief
cd chief
# Install dependencies
bun install
# Create an alias (add to your shell profile)
alias chief="bun run /path/to/chief/src/index.ts"chief planThis will:
- Prompt you to describe what you want to build (multiline)
- Start an interactive planning session with Claude
- Write the plan to
.chief/plans/YYYY-MM-DD-<feature-name>.md
Use Enter for a new line and Cmd+Enter to submit.
# Pick a plan from .chief/plans
chief breakdown
# Or specify the feature name
chief breakdown <feature-name>
# Alias
chief bdCreates .chief/tasks/YYYY-MM-DD-<feature-name>.tasks.json from the plan.
# Pick a task set from .chief/tasks
chief run
# Or specify the feature name
chief run <feature-name>
# Run once interactively
chief run --singleChief will:
- Check out a
feature/<feature-name>branch - Run Claude to complete tasks (loop mode by default)
- Verify the work using your configured verification steps
- Mark tasks as done and commit
- Push changes and create a pull request
Chief uses a local .chief/ directory in your repository:
.chief/plans/- Plans (YYYY-MM-DD-<feature-name>.md).chief/tasks/- Tasks (YYYY-MM-DD-<feature-name>.tasks.json).chief/verification.txt- Verification steps
Git-ignoring .chief/ is optional.
On first run, Chief will prompt you to pick verification steps based on package.json scripts, with an option to add custom steps.
Example:
- bun run lint
- bun run typecheck
- bun run test
Tasks in *.tasks.json follow this structure:
[
{
"category": "Feature",
"description": "Implement user authentication",
"passes": false,
"steps": [
"Create auth middleware",
"Add login endpoint",
"Add session management"
]
}
]Chief implements the Ralph Wiggum methodology:
- Plan - Use AI to create a concise implementation plan through conversation
- Break Down - Convert the plan into discrete, verifiable tasks
- Execute - Run AI in a loop to complete tasks one at a time
- Verify - Use automated checks (tests, lint, typecheck) to verify work
- Ship - Push changes and create a PR when done
Each task is completed in isolation, committed separately, making it easy to review and revert if needed.
MIT
