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namuh-eng/ralph-to-ralph

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A three-phase autonomous pipeline that inspects any SaaS product, builds a working clone with real cloud infrastructure, and QA-tests everything — no human in the loop.

概览

A three-phase autonomous pipeline that inspects any SaaS product, builds a working clone with real cloud infrastructure, and QA-tests everything — no human in the loop.

README


Note for AI agents: This README is structured as step-by-step instructions you can follow to set up and run the pipeline for a user. Each step includes verification commands. If you’re an agent reading this, start at Setup.


Proof It Works

We pointed Ralph-to-Ralph at resend.com during Ralphthon Seoul 2026 and walked away (see the result: opensend):

Metric Result
Features built 52
Lines of code 24,000+
Unit tests passing 388
Dashboard pages 10
API endpoints 16+
Total time ~4 hours (fully autonomous)
Human intervention Zero

The clone sends real emails via AWS SES, verifies real domains, auto-configures DNS via Cloudflare, and deployed itself to AWS App Runner. It placed 2nd at the hackathon.


How It Works

A single watchdog orchestrator (ralph/ralph-watchdog.sh) drives four phases. It auto-restarts failures, tracks token cost against a budget cap, refuses to enter QA until the workspace proves it builds, and detects zero-progress QA stalls. Up to 5 build-QA cycles per feature.

Every loop phase is backed by either Codex (default, reasoning_effort=low — empirically best across all four loops) or Claude. You pick during onboarding; the choice lands in ralph-config.json as inspectAgent / buildAgent / qaAgent / architectureAgent (plus reasoningEffort for codex), and each loop reads its own field at runtime.

Phase Agent What It Does
1. Inspect configurable (default: Codex) + Ever CLI Browses the target, scrapes docs deterministically (Scrapling + trafilatura), captures screenshots, generates a PRD with 50+ features
1.5. Architecture configurable (default: Codex) Turns the PRD into evidence-based decisions — process topology, data model, infra, auth, packaging — recorded in ralph/architecture-decisions.json
2. Build configurable (default: Codex) For each feature: vertically slices it into ≤4 testable phases (Phase 2.5), then implements each slice TDD-first, commits and pushes after every slice
3. QA configurable (default: Codex) + Ever CLI Per-feature progressive disclosure: Functional → API Contract → Security → Accessibility. Fixes bugs and re-tests until features pass

Prerequisites

You can install these ahead of time, or onboarding will prompt you when it needs them.

Coding CLI

The agent that drives Inspect, Architecture, Build, and QA. You pick one during onboarding and the choice applies to every loop.

Tool Install
Codex CLI (default — reasoning_effort=low) npm install -g @openai/codex
Claude Code CLI npm install -g @anthropic-ai/claude-code

Codex at low reasoning effort is the empirical best across every loop and is the default. You can override per phase by editing inspectAgent / buildAgent / qaAgent / architectureAgent in ralph-config.json after onboarding — the loop scripts read those fields at runtime via ralph/lib/agent-runner.sh.

Browser Agent

Used by Inspect and QA to drive the target product and your clone.

Tool Install
Ever CLI (recommended — the loop is tuned for this) See foreverbrowsing.com
Agent Browser See agent-browser.dev
Playwright npm install -g playwright && playwright install

Anything else with a CLI works, but the inspect and QA prompts are tuned for Ever CLI — expect rougher edges with other agents.

Cloud CLI

Pick one and authenticate it. Onboarding will ask if it doesn’t find one already installed.

Provider Install Authenticate
Vercel (default, personal) npm install -g vercel vercel login
AWS (team / production) brew install awscli aws configure
GCP Install gcloud gcloud auth login
Azure Install az az login

Want Railway, Fly.io, Render, or self-hosted? Pick “custom” during onboarding and describe your stack — onboarding generates a stack-specific preflight script.


Stack

Onboarding picks one of three first-class stacks based on your answers (language + framework), writes the choice to ralph-config.json, and runs the matching template’s setup script.

Stack Language Framework Tests Linter
typescript-nextjs (default, most complete) TypeScript Next.js + React + Tailwind Vitest + Playwright Biome
python-fastapi Python FastAPI + uvicorn pytest + httpx Ruff
go-chi Go chi router go test go test (no separate linter)

The TypeScript template ships the most pre-wired tooling — Drizzle for DB, Playwright for E2E, full make test-e2e and make db-push targets. Python and Go templates are minimal scaffolds; the build agent installs database drivers and feature-specific dependencies as the PRD requires them.

After onboarding, .ralph-setup-done records the template name and BUILD_GUIDE.md (in the repo root) has stack-specific build instructions. Templates live in .claude/skills/ralph-to-ralph-onboard/templates/.


Setup

Follow these steps in order. Each step has a verification command — run it before moving to the next step.

Step 1: Clone and install

Step 1 — Fork this repo on GitHub (top-right “Fork” button). This gives you your own copy to push SaaS features into, and lets you pull pipeline improvements from upstream later.

Step 2 — Clone your fork:

git clone https://github.com/YOUR_USERNAME/ralph-to-ralph.git
cd ralph-to-ralph

# Optional: track upstream for future pipeline improvements
git remote add upstream https://github.com/namuh-eng/ralph-to-ralph.git

Then continue:

Verify:

ls ralph-config.json 2>/dev/null || echo "No config yet (expected — created by onboarding)"
ls .ralph-setup-done 2>/dev/null || echo "Stack not set up yet (expected — done by onboarding)"

Step 2: Configure environment

cp .env.example .env

Then set these values in .env:

Variable Required Where to get it
ANTHROPIC_API_KEY Yes (if clone has AI features) console.anthropic.com
DASHBOARD_KEY Yes Generate with openssl rand -hex 32
DATABASE_URL Set by onboarding Auto-configured during onboarding
CLOUDFLARE_API_TOKEN Optional (DNS automation) Cloudflare dashboard
CLOUDFLARE_ZONE_ID Optional (DNS automation) Cloudflare dashboard → your domain → Overview

Verify:

# Check that .env exists and has content
test -f .env && echo ".env exists" || echo "ERROR: .env missing"
grep -c '=' .env  # Should show number of configured variables

Step 3: Onboard a target product

Onboarding researches the target product, configures the stack, installs dependencies, and starts the build loop.

Open this repo in your coding agent and invoke the onboarding skill:

Agent Invoke with
Claude Code /ralph-to-ralph-onboard
Codex $ralph-to-ralph-onboard
Other CLIs Paste the contents of .claude/skills/ralph-to-ralph-onboard/SKILL.md and ask the agent to follow it

The agent researches the product live, explains what needs to be set up in plain English, walks you through each decision, installs anything missing (browser agent, cloud CLI), and verifies your setup before kicking off the build loop. This is the path we recommend — it adapts to whatever’s already on your machine.

Alternative: Script

./ralph/onboard.sh

A bash script that asks for target URL, clone name, cloud provider, deploy preference, and browser agent — then hands off to Claude for research and config generation. Useful for non-interactive environments. Produces the same ralph-config.json as the skill.

Verify onboarding completed:

# Config exists and has required fields
python3 -c "
import json, sys
c = json.load(open('ralph-config.json'))
required = ['targetUrl', 'targetName', 'language', 'stackProfile']
missing = [k for k in required if k not in c]
if missing:
    print(f'FAIL: missing fields: {missing}', file=sys.stderr)
    sys.exit(1)
print(f'OK: target={c[\"targetUrl\"]}, lang={c[\"language\"]}, stack={c[\"stackProfile\"]}')
"

# Stack is set up and project compiles
test -f .ralph-setup-done && echo "Stack: $(cat .ralph-setup-done)"
make check && make test

Architecture Reference

Pipeline Flow

./ralph/onboard.sh                      # Onboard → ralph-config.json
    ↓
./ralph/ralph-watchdog.sh               # Orchestrator (cost cap, build-proof gate)
    ↓
┌─────────────────────────────────────────────────────┐
│  Phase 1: INSPECT (Claude + Ever CLI)               │
│  → Browse target, scrape docs (Scrapling)           │
│  → Generate prd.json (50+ features)                 │
└────────────────────────┬────────────────────────────┘
                         ↓
┌─────────────────────────────────────────────────────┐
│  Phase 1.5: ARCHITECTURE (Claude architect)         │
│  → PRD → architecture-decisions.json                │
│  → Topology, data model, infra, auth, packaging     │
└────────────────────────┬────────────────────────────┘
                         ↓
┌─────────────────────────────────────────────────────┐
│  Phase 2: BUILD (Claude, one feature at a time)     │
│   ├─ Phase 2.5 Structure: vertical slice ≤4 phases  │
│   ├─ TDD: tests first, then implement               │
│   └─ make check && make test → commit → push        │
└────────────────────────┬────────────────────────────┘
                         ↓
┌─────────────────────────────────────────────────────┐
│  Phase 3: QA (Codex + Ever CLI)                     │
│  → Functional / API Contract / Security / A11y      │
│  → Fix and re-test (up to 5 cycles)                 │
└────────────────────────┬────────────────────────────┘
                         ↓
                All features pass? → Deploy
                No?                → Back to Phase 2

File Map

ralph-to-ralph/
├── ralph/
│   ├── onboard.sh                 # Onboarding script (alternative to the skill)
│   ├── onboard-prompt.md          # Onboarding agent instructions
│   ├── ralph-watchdog.sh          # Orchestrator: inspect → architecture → build → QA
│   ├── inspect-ralph.sh           # Phase 1 runner
│   ├── build-ralph.sh             # Phase 2 runner
│   ├── qa-ralph.sh                # Phase 3 runner — assembles prompt from ralph/qa/*.md
│   ├── inspect-prompt.md          # Inspect agent instructions
│   ├── inspect-spec.md            # Inspection strategy
│   ├── architecture-prompt.md     # Architect agent instructions (Phase 1.5)
│   ├── build-prompt.md            # Build agent instructions
│   ├── structure-prompt.md        # Vertical-slicing instructions (Phase 2.5, invoked by Build)
│   ├── qa/                        # Modular QA prompts: base, api, security, a11y, footer
│   ├── pre-setup.md               # Pre-configured setup (read by all agents)
│   ├── ever-cli-reference.md      # Ever CLI command reference
│   ├── deployment-profiles.json   # fast-starter / production-aws / advanced-custom
│   ├── ralph-state.schema.json    # Watchdog state schema (validated by `make validate`)
│   ├── ralph-state.template.json  # Empty state template
│   └── docs/                      # Architecture diagram + supporting docs
├── .claude/skills/
│   └── ralph-to-ralph-onboard/    # Interactive onboarding skill (Claude Code)
│       ├── SKILL.md               # Skill definition + flow
│       ├── references/            # Long-form prompt fragments
│       ├── scripts/setup-stack.sh # Generic stack scaffolding script
│       └── templates/             # Stack templates: typescript-nextjs, python-fastapi, go-chi
├── schemas/                       # JSON schemas validated by `make validate`
│   ├── ralph-config.schema.json
│   ├── prd-item.schema.json
│   ├── qa-report-entry.schema.json
│   └── architecture-decision.schema.json
├── scripts/
│   ├── start.sh                   # Thin restart wrapper around the watchdog
│   ├── preflight.sh               # Provisions cloud infrastructure
│   ├── generate-demo-keys.sh      # Generates API keys for demos
│   ├── validate-schemas.mjs       # Validates state files against JSON schemas
│   └── scrape-docs.py             # Deterministic doc scraper (Scrapling + trafilatura)
├── src/                           # Source code (scaffolded by onboarding)
├── tests/                         # Unit tests + factories + watchdog verification
├── tests/e2e/                     # E2E tests
├── packages/sdk/                  # SDK package (if target product has one)
├── hack/run_silent.sh             # Output formatter used by Makefile
├── agent_docs/learnings/          # Long-running notes from past clone runs
├── docker-compose.dev.yml         # Local dev stack: Postgres, Redis, Mailpit
├── .env.example                   # Documented environment variables
├── ralph-config.json              # Generated by onboarding (single source of truth)
├── prd.json                       # Product requirements (generated by Inspect phase)
├── BUILD_GUIDE.md                 # Stack-specific build instructions (from template)
├── CLAUDE.md                      # Instructions for Claude agents (Build)
├── AGENTS.md                      # Instructions for Codex agent (QA)
├── Makefile                       # Contract targets — real recipes appended by onboarding
└── .ralph-setup-done              # Marker file — contains template name

Commands

Command What It Does
make check Typecheck + lint/format (composite)
make test Run unit tests
make test-e2e Run E2E tests (needs dev server)
make all check + test
make fix Auto-fix lint/format issues
make validate Validate state files (prd.json, qa-report.json, ralph-config.json, ralph/ralph-state.json) against their JSON schemas
make dev Dev server on port 3015
make build Production build
make db-push / db-generate / db-migrate Schema sync · generate migration · run migrations
make typecheck / lint / format / clean Granular targets — usually run via make check

Pass VERBOSE=1 (or use make check-verbose / test-verbose) to see full output instead of the silent-on-success summary.

Agent Roles

Agent What It Reads What It Produces Phase
Onboarding (Claude) ralph/onboard-prompt.md, ralph/pre-setup.md, CLAUDE.md ralph-config.json, installed deps, rewritten config files Pre-loop
Inspect (Claude + Ever CLI) ralph/inspect-prompt.md, ralph/inspect-spec.md, ralph/ever-cli-reference.md prd.json, screenshots in ralph/screenshots/inspect/ Phase 1
Architect (Claude) ralph/architecture-prompt.md, prd.json, target-docs/, ralph-config.json ralph/architecture-decisions.json, updated build-spec.md Phase 1.5
Build (Claude) ralph/build-prompt.md, ralph/structure-prompt.md, prd.json, build-spec.md, CLAUDE.md Source in src/, tests in tests/, SDK in packages/sdk/, structure outlines in .qrspi/{feature-id}/structure.md (when needed) Phase 2 (+2.5 Structure inline)
QA (Codex + Ever CLI, multi-layer) AGENTS.md, ralph/qa/{base,api,security,a11y,footer}.md, ralph/ever-cli-reference.md Bug fixes, QA screenshots in ralph/screenshots/qa/, qa-report.json Phase 3

The QA agent uses progressive disclosure — qa-ralph.sh assembles the prompt from the modules above based on feature category (auth, crud, infrastructure, settings, etc.). Not every feature runs all four sub-phases.

What Gets Built

The pipeline produces a fully functional, deployed product — not a mockup.

Capability Implementation When
Full-stack app Language + framework from ralph-config.json Always
REST API Bearer token auth Always
Database Postgres (ORM depends on language) Always
Unit + E2E tests Stack-specific test runner + E2E framework Always
Deployment Docker + cloud provider Always (unless skipDeploy: true)
Email delivery AWS SES / SendGrid If the target sends emails
DNS management Cloudflare API If the target manages domains
File storage AWS S3 / Cloud Storage If the target handles uploads
SDK package Language-native SDK If the target has an SDK

Customization

Changing the target product

Re-run onboarding. Easiest in your coding agent:

Agent Invoke with
Claude Code /ralph-to-ralph-onboard
Codex $ralph-to-ralph-onboard

For a clean slate (clears ralph-config.json and .ralph-setup-done), use the script form:

./ralph/onboard.sh --reset   # Clear previous config
./ralph/onboard.sh            # Start fresh

Modifying agent behavior

The pipeline is controlled by prompt files:

File Controls
ralph/onboard-prompt.md How the Onboarding agent researches the target and configures the stack
ralph/inspect-prompt.md How the Inspect agent browses, scrapes docs, and writes the PRD
ralph/architecture-prompt.md How the Architect turns the PRD into evidence-based architecture decisions
ralph/build-prompt.md How the Build agent implements features (TDD, package install rules, etc.)
ralph/structure-prompt.md How Build vertically slices large features into ≤4 testable phases
ralph/qa/{base,api,security,a11y,footer}.md How the QA agent tests features — modules assembled per feature category
ralph/pre-setup.md Pre-configured setup context (read by all agents)

Running phases individually

The watchdog (ralph/ralph-watchdog.sh) is the production entry point — it handles process-level restarts, cost caps, build-proof gating before QA, and stall detection. Run a single phase only when iterating manually:

./ralph/inspect-ralph.sh    # Phase 1 only — generate / refresh prd.json
./ralph/build-ralph.sh                  # Phase 2 only — needs prd.json
./ralph/qa-ralph.sh                     # Phase 3 only — needs a built clone

These scripts have no process-level restart logic — if they crash, they stay crashed. Fine for short sessions; for unattended end-to-end runs, always use the watchdog.


FAQ


Contributing

We welcome contributions — bug fixes, new features, documentation, or new target product test runs.

  1. Fork the repository
  2. Create a feature branch (git checkout -b my-feature)
  3. Make your changes
  4. Run make check && make test to verify
  5. Commit with a clear message
  6. Open a pull request

If you’re unsure about a change, open an issue first to discuss it.

Team

Ralph-to-Ralph was built by:

Built at Ralphthon Seoul 2026.


Inspiration

Inspired by @GeoffreyHuntley’s “software eats itself” post.

License

Apache License 2.0 — use it, modify it, ship it. Includes an explicit patent grant.

View this README on GitHub

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安装

npx skillfish add namuh-eng/ralph-to-ralph