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PRD-based task tracking CLI for AI coding agents. Run agents headlessly with structured task tracking and progress visibility.

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rem4ik4ever/ralph

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Ralph

PRD-based task tracking CLI for AI coding agents. Run agents headlessly with structured task tracking and progress visibility.

Inspired by Geoff Huntley's ralph technique - putting a coding agent in a while loop and letting it work autonomously.

Installation

# npm
npm install -g rlph-cli

# or run directly
npx rlph-cli prd add my-feature.md my-feature

From source

git clone https://github.com/rem4ik4ever/ralph.git
cd ralph
bun install
bun run build
bun link

Usage

Initialize Project

Set up ralph in your project and install Claude Code skills:

ralph init

Creates .ralph/ directory and installs skills to ~/.claude/skills/:

  • ralph-prd - PRD creation skill
  • ralph - CLI documentation skill

Add a PRD

Convert markdown PRD to trackable JSON tasks:

ralph prd add <path> <name> [--agent claude]

Example:

ralph prd add .ralph/prd/my-feature/prd.md my-feature

Creates:

  • prd.json - converted tasks with pass/fail tracking
  • progress.txt - cross-iteration memory

List PRDs

View all PRDs with status:

ralph prd list

Output:

NAME           STATUS        PROGRESS  LOCATION
my-feature     in_progress   3/7       local
refactor-api   pending       0/4       global

Show PRD Info

Display PRD details and file locations:

ralph prd info <name>

Output:

PRD: my-feature
Status: in_progress (3/7 tasks complete)

Files:
  prd.md:      .ralph/prd/my-feature/prd.md
  prd.json:    .ralph/prd/my-feature/prd.json
  progress:    .ralph/prd/my-feature/progress.txt
  iterations:  .ralph/prd/my-feature/iterations/ (2 files)

Delete PRD

Remove a PRD and all associated files:

ralph prd delete <name>
ralph prd delete <name> --force  # skip confirmation

Run PRD

Execute agent loop against a PRD:

ralph run <prd-name> [--agent claude] [--iterations 4]

Example:

ralph run my-feature -i 10

Agent picks up next incomplete task, implements it, runs feedback loops (tests/lint/types), marks task passed, repeats until done.

How it works

  1. ralph init sets up project and installs Claude Code skills
  2. Write markdown PRD (or use ralph-prd skill in Claude Code)
  3. ralph prd add converts markdown to JSON tasks
  4. ralph run loops agent against PRD tasks
  5. Agent updates prd.json passes field on completion
  6. Agent maintains progress.txt with learnings across iterations
  7. Stops when all tasks pass or max iterations reached
  8. ralph prd info shows progress and file locations

PRD folder structure

Local PRDs (in project):

.ralph/
├── config.json   # Project configuration
└── prd/<name>/
    ├── prd.md        # Original markdown
    ├── prd.json      # Tasks with passes field
    ├── progress.txt  # Cross-iteration memory
    └── iterations/   # Iteration logs

Global PRDs (fallback):

~/.ralph/prd/<name>/
└── ...

Local PRDs take precedence over global when both exist.

Supported agents

  • claude - Claude Code CLI (requires claude installed)

Requirements

  • Node.js >= 18
  • Claude Code CLI installed and authenticated

Releases

This project uses semantic-release for automated versioning and npm publishing.

How it works

  1. Push/merge to main triggers release workflow
  2. Commits are analyzed to determine version bump
  3. CHANGELOG.md is updated automatically
  4. Package is published to npm
  5. GitHub release is created

Conventional Commits

Commit messages must follow Conventional Commits:

<type>(<scope>): <description>

[optional body]

[optional footer]
Type Version Bump Example
fix Patch (1.0.x) fix(cli): handle empty input
feat Minor (1.x.0) feat(prd): add export command
feat! or BREAKING CHANGE: Major (x.0.0) feat!: change config format

Other types (docs, chore, refactor, test, ci) don't trigger releases.

License

MIT

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PRD-based task tracking CLI for AI coding agents. Run agents headlessly with structured task tracking and progress visibility.

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