---
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