Ralph is an autonomous coding loop that repeatedly runs AI coding tools until the items in a product requirements document are complete. Developers use it in Git repositories with tools such as Amp or Claude Code, while progress persists through files and git history. Its catalogue add-ons help create requirements documents and convert them into the format Ralph executes.
Borrowing it
Nothing to install: this file belongs to snarktank/ralph. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/snarktank/ralph/main/AGENTS.mdgit clone --depth 1 https://github.com/snarktank/ralphWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/snarktank/ralph/agents-md)<a href="https://agentmods.dev/instructions/snarktank/ralph/agents-md"><img src="https://agentmods.dev/badge/instructions/snarktank/ralph/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/snarktank/ralph/agents-md"><img src="https://agentmods.dev/badge/instructions/snarktank/ralph/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00329 | $0.00329 |
| Opus 5.5 | $0.00132 | $0.00132 |
| Sonnet 5.5 | $0.00066 | $0.00066 |
| Haiku 4.5 | $0.00033 | $0.00033 |
Grade A, and why
ralph AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Ralph Agent Instructions
Overview
Ralph is an autonomous AI agent loop that runs AI coding tools (Amp or Claude Code) repeatedly until all PRD items are complete. Each iteration is a fresh instance with clean context.
Commands
# Run the flowchart dev server
cd flowchart && npm run dev
# Build the flowchart
cd flowchart && npm run build
# Run Ralph with Amp (default)
./ralph.sh [max_iterations]
# Run Ralph with Claude Code
./ralph.sh --tool claude [max_iterations]
Key Files
ralph.sh- The bash loop that spawns fresh AI instances (supports--tool ampor--tool claude)prompt.md- Instructions given to each AMP instanceCLAUDE.md- Instructions given to each Claude Code instanceprd.json.example- Example PRD formatflowchart/- Interactive React Flow diagram explaining how Ralph works
Flowchart
The flowchart/ directory contains an interactive visualization built with React Flow. It's designed for presentations - click through to reveal each step with animations.
To run locally:
cd flowchart
npm install
npm run dev
Patterns
- Each iteration spawns a fresh AI instance (Amp or Claude Code) with clean context
- Memory persists via git history,
progress.txt, andprd.json - Stories should be small enough to complete in one context window
- Always update AGENTS.md with discovered patterns for future iterations
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 48 lines · 329 tokens per session scan A 82d11c28ace5
ralph AGENTS.md is an instructions file published in the GitHub repository snarktank/ralph (22,078 stars, last pushed 8mo ago), licensed MIT. It adds 329 tokens to every session, about $0.0013 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
vscode model-prompts.instructions.md
Model-specific prompt authoring and registry guidelines.