Coding & Developmentβ¨geminiπ€claudeβ¨οΈcursorπuniversal
Ralph CLI
Making it easy to use Ralph with a simple set of CLI tools. Works with Amp, Claude, Codex, Cursor, Droid, and Gemini.
Quick Start
Install this Skill
npx skills add yemyat/ralph-cli# Ralph CLI
A command-line tool for managing **Ralph Wiggum** AI development workflows across projects.
Based on the [Ralph Wiggum Technique](https://github.com/ghuntley/how-to-ralph-wiggum) - an AI development methodology that uses autonomous coding loops with AI agents.
This implementation takes a **task-first approach**: instead of giving agents autonomy to work through specs, we decompose specs into small tasks during planning, then feed tasks to agents one at a time. Smaller tasks keep agents focused and out of the "dumb zone."
> **Meta**: This CLI was built by pointing an AI agent at the [Ralph Wiggum technique repo](https://github.com/ghuntley/how-to-ralph-wiggum), then using Ralph itself to implement and refine the tool. Recursive AI development in action.
## Installation
```bash
bun install -g ralph-wiggum-cli
```
Or with npm:
```bash
npm install -g ralph-wiggum-cli
```
For local development:
```bash
git clone <repo>
cd ralph-cli
bun install
bun link
```
## AI Agent Skills
Ralph includes a skill file that teaches AI agents how to use the CLI.
### Claude Code
```bash
cp -r .claude/skills/ralph ~/.claude/skills/
```
## Quick Start
```bash
# Initialize Ralph in your project
cd your-project
ralph-wiggum-cli init
# Run planning mode (analyzes specs and creates implementation.json)
ralph-wiggum-cli plan
# Run build mode (executes tasks from implementation.json)
ralph-wiggum-cli build
# View status
ralph-wiggum-cli status
# Stop a running session
ralph-wiggum-cli stop
```
## Commands
| Command | Description |
| ------------------------- | ---------------------------------------------- |
| `ralph-wiggum-cli init` | Initialize Ralph in the current project |
| `ralph-wiggum-cli plan` | Run planning mode (analyze specs, create plan) |
| `ralph-wiggum-cli build` | Run build mode (execute tasks from plan) |
| `ralph-wiggum-cli stop` | Stop running session |
| `ralph-wiggum-cli status` | Show project status and sessions |
| `ralph-wiggum-cli agents` | List available AI agents |
## Options
### Init Options
```bash
ralph-wiggum-cli init [options]
-a, --agent <agent> AI agent for both modes (default: claude)
-m, --model <model> Model for both modes
--plan-agent <agent> AI agent for planning mode
--plan-model <model> Model for planning mode
--build-agent <agent> AI agent for building mode
--build-model <model> Model for building mode
-f, --force Force reinitialization
```
### Plan/Build Options
```bash
ralph-wiggum-cli plan [options]
ralph-wiggum-cli build [options]
-a, --agent <agent> Override the configured agent
-m, --model <model> Override the configured model
-v, --verbose Enable verbose output (shows agent stdout/stderr)
```
## Supported Agents
| Agent | Description |
| ---------- | -------------------------------------------------------------------------- |
| `claude` | [Claude Code](https://docs.anthropic.com/en/docs/claude-code) by Anthropic |
| `amp` | [Amp Code](https://ampcode.com) by Sourcegraph |
| `droid` | [Factory Droid](https://factory.ai) CLI |
| `opencode` | [OpenCode](https://opencode.ai) CLI |
| `cursor` | [Cursor Agent](https://cursor.com) CLI |
| `codex` | [OpenAI Codex](https://openai.com/codex) CLI |
| `gemini` | [Gemini CLI](https://ai.google.dev/gemini-api) by Google |
| `pi` | [Pi](https://github.com/mariozechner/pi-coding-agent) coding agent |
## Project Structure
After `ralph-wiggum-cli init`, your project will have:
```
your-project/
βββ .ralph-wiggum/
βββ config.json # Project config and session history
βββ PROMPT_plan.md # Planning mode prompt (customizable)
βββ implementation.json # Task tracking (generated by plan mode)
βββ GUARDRAILS.md # Compliance rules (before/after checks)
βββ PROGRESS.md # Audit trail of completed work
βββ specs/ # Specification files
β βββ example.md # Example spec template
βββ logs/ # Session logs (gitignored)
```
## How It Works
This CLI implements a **task-first variation** of the Ralph Wiggum technique.
Traditional Ralph implementations give agents autonomy to pick tasks and work spec-by-spec. This approach is different: we break specs into small, focused tasks during planning, then feed them to the agent one at a time during building.
**Why task-first?**
- **Smaller context = smarter agent.** Large specs push agents into the "dumb zone" where they lose focus and make mistakes. Small tasks keep them sharp.
- **Deterministic executio
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