AI agent loop. Each task runs in a fresh invocation — no context pollution.
RalphVideo.mp4
npx ralph-template ralphThen tell your AI what tasks to create:
Read ralph/README.md and create a ralph setup for [YOUR GOAL].
[Describe what needs to be done.]
Do NOT execute any tasks — only create the plan files.
This populates fix_plan.md with checkbox tasks. That's it — the AI must not run any task yet.
cd ralph && npm start 20Ralph picks up tasks one by one, each in a fresh invocation. Open fix_plan.md to watch them get ticked off.
| File | Purpose |
|---|---|
fix_plan.md |
Task checklist. One - [ ] = one iteration |
specs/ |
Extra context for tasks that need it |
AGENT.md |
Project config and quality standards |
PROMPT.md |
Loop logic — don't modify |
README.md |
Setup instructions (for you and the AI) |
Recipes are pre-packaged setups for common tasks. Instead of manually writing specs and describing your goal each time, a recipe scaffolds ralph with everything pre-configured — specs, AI instructions, all of it.
npx ralph-template ralph --recipe llms-txtThis creates ralph/ with the recipe's specs already in specs/ and recipe-specific instructions baked into README.md. Then tell your AI:
Read ralph/README.md and create a plan. Do NOT execute any tasks.
The AI reads the README, sees the recipe instructions, analyzes your project, and creates fix_plan.md. You watch it work, then run cd ralph && npm start 20.
To see all available recipes:
npx ralph-template --list-recipes| Recipe | Description |
|---|---|
llms-txt |
Add hierarchical llms.txt documentation to a project |
llms-txt-general |
Create hierarchical llms.txt documentation for any subject (website, book, API, docs, etc.) |
self-improve |
Analyze, evaluate, and implement clear-win improvements for any part of a project |
A recipe is a folder inside recipes/ with this structure:
recipes/my-recipe/
├── recipe.json # name + description
├── instructions.md # AI planning instructions (injected into README)
└── specs/ # reference files the AI needs
└── my-guide.md
Step 1 — Create the folder:
mkdir -p recipes/my-recipe/specsStep 2 — Add recipe.json with a name and description:
{
"name": "my-recipe",
"description": "Short description of what this recipe does"
}Step 3 — Add instructions.md with AI planning instructions. This gets injected into the README's "AI Setup Instructions" section, telling the AI exactly what to plan. Example:
### Recipe: My Recipe Name
Read `specs/my-guide.md` to understand the approach.
Analyze the project. Then create tasks in `fix_plan.md` to [describe the goal].
Each task should [describe the task granularity].Step 4 — Add spec files to specs/. These are reference materials the AI reads while creating the plan (guides, conventions, examples).
Step 5 (optional) — Add a custom AGENT.md to override the default agent instructions for task execution.
That's it. Now npx ralph-template ralph --recipe my-recipe will scaffold ralph with your specs and instructions ready to go.
npm run ralph:save -- my-task # save
npm run ralph:load -- my-task # restore
npm run ralph:list # list all
npm run ralph:new # reset to blank