--- name: ralph-runner description: Run Ralph Wiggum autonomous coding loops. Use when user asks to run ralph, start autonomous coding, execute a PRD, implement features from a task list, or wants Claude Code to work through user stories iteratively. license: MIT compatibility: Requires ralph-cli and Claude Code CLI installed metadata: author: linuxlewis version: "1.0.0" --- # Ralph Runner Run autonomous AI coding loops that implement features from a PRD (Product Requirements Document) iteratively. ## Prerequisites - **Claude Code** - `claude --version` - **ralph-cli** - `ralph --version` ## Quick Start ```bash # Check status of a PRD ralph status prd.json # Run the loop ralph run prd.json # With context files ralph run prd.json --context AGENTS.md --context ./docs # More iterations ralph run prd.json --iterations 20 ``` ## Workflow ### 1. Create PRD Create a `prd.json` file with user stories: ```json { "project": "MyApp", "branchName": "ralph/feature-name", "description": "Feature description", "userStories": [ { "id": "US-001", "title": "Add login form", "priority": 1, "passes": false } ] } ``` ### 2. Run Ralph ```bash ralph run prd.json --context AGENTS.md ``` ### 3. Monitor Progress ```bash ralph status prd.json ``` ## How It Works Each iteration: 1. Reads `prd.json`, picks highest priority story where `passes: false` 2. Spawns fresh Claude Code instance 3. Claude implements that ONE story 4. Runs quality checks (typecheck, lint, tests) 5. If passing: commits, updates `prd.json`, appends to `progress.txt` 6. Outputs `COMPLETE` when all done Memory persists via: - Git history (commits) - `progress.txt` (learnings) - `prd.json` (status) ## CLI Reference ### `ralph run ` ```bash ralph run prd.json [options] Options: -i, --iterations Max iterations (default: 10) -c, --context Context files/dirs to include -p, --prompt Custom prompt template --headed Show Claude output live --dry-run Preview without running ``` ### `ralph status [prd]` ```bash ralph status prd.json ``` Shows progress bar and story status. ## PRD Format See [references/prd-format.md](references/prd-format.md) for complete format specification. ## Best Practices 1. **Keep stories small** - Each should complete in one context window 2. **Good acceptance criteria** - Be specific about "done" 3. **Include typecheck** - Add "Typecheck passes" to criteria 4. **Use context** - Pass in AGENTS.md and relevant docs 5. **Check progress.txt** - Contains learnings from previous iterations