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Stitchflow

Stitchflow

AI UI design that actually understands your project — not generic AI slop

🇨🇳 简体中文

Platform Python Agent Skills Standard License Compatible


Demo

Stitchflow Demo

▶ 观看完整演示视频(18秒)


The Problem

Ask any AI coding agent to "design a dashboard," and you'll get something. But it'll look like every other AI-generated UI — generic layouts, the same color schemes, the same "AI aesthetic." It doesn't know your brand. It doesn't understand your business. It hasn't read your product specs.

The result: code that looks fine at first glance, but feels hollow and unoriginal the moment you use it.

What Stitchflow Does Differently

Stitchflow doesn't just pass your one-liner to an LLM and dump out code. It runs a six-stage pipeline that starts with understanding your project and ends with production-ready frontend code:

  1. Reads your project — CLAUDE.md, brand data, product specs, existing UI — so it knows what you're building
  2. Crafts a tailored prompt — not a template fill-in-the-blank, but a prompt written specifically for your business domain, brand colors, user personas, and functional needs
  3. Drives Google Stitch via CDP — connects to your already-logged-in Chrome browser, selects the "Web" platform, auto-picks the strongest available model, types in the prompt, and kicks off generation
  4. Captures the result — full-page screenshot for your review
  5. Exports HTML/CSS — extracts the rendered design from Stitch
  6. Converts to real code — your AI agent maps the design to your actual stack (React, Vue, plain HTML) with your project's conventions

The output isn't "an AI dashboard." It's your dashboard, for your brand, with your data.

Installation

# 1. Install dependencies
pip install playwright && playwright install chromium

# 2. Log into your Google account in Chrome, then visit https://stitch.withgoogle.com/ once to authorize

# 3. Install to your AI coding agent
# Claude Code:
cp -r stitchflow ~/.claude/skills/

# Codex CLI:
cp -r stitchflow ~/.agents/skills/

# OpenClaw:
openclaw skill install --path ./stitchflow

# Cursor / Hermes / Gemini CLI:
cp -r stitchflow ~/.cursor/skills/     # Cursor
cp -r stitchflow ~/.hermes/skills/     # Hermes
cp -r stitchflow .agents/skills/       # Gemini CLI

Usage

With your AI agent (recommended)

After installation, just say:

"Design an e-commerce operations dashboard with dark theme"

Your AI agent handles the entire pipeline — from reading your project context to delivering the final screenshot. Approve it, and it exports the code.

CLI mode

# First time: launch CDP-enabled Chrome (closes existing Chrome windows)
python3 stitch.py --launch-chrome

# Generate a design
python3 stitch.py "your full design prompt" --output dashboard.png

# Full pipeline (launch + generate + export)
python3 stitch.py "your prompt" --launch-chrome --output dashboard.png --export .stitch/designs/

Six-Stage Pipeline

Project Context → Tailored Prompt → Stitch Generation → Screenshot Review → Export HTML → AI Writes Code
Stage Who What
1. Understand AI Read CLAUDE.md, product data, brand assets, existing UI
2. Prompt AI Write a Stitch prompt with brand colors, personas, page structure, feature requirements
3. Launch Script Kill existing Chrome → clone profile (preserves login) → restart in CDP mode
4. Generate Script Connect CDP → open Stitch home → select "Web" → auto-switch best model → type prompt → press Enter → poll until done
5. Review AI Show screenshot to user, get approval or revision feedback
6. Ship Script+AI Export HTML/CSS → AI reads → converts to React/Vue/static code

Cross-Platform

macOS Windows Linux
Chrome Path /Applications/Google Chrome.app/... %PROGRAMFILES%\Google\Chrome\... google-chrome (PATH)
Profile Path ~/Library/Application Support/Google/Chrome %LOCALAPPDATA%\Google\Chrome\User Data ~/.config/google-chrome
Special Flags None --disable-features=DevToolsDebuggingRestrictions None

Multi-Agent Compatibility

One SKILL.md, compatible across all major AI coding agents (follows agentskills.io open standard):

Agent Install Path Invocation
Claude Code ~/.claude/skills/ /stitchflow
Codex CLI ~/.agents/skills/ $stitchflow
OpenClaw openclaw skill install stitchflow
Hermes ~/.hermes/skills/ Auto-detect
Cursor ~/.cursor/skills/ Auto-detect
Gemini CLI .agents/skills/ Auto-detect

Model Selection

Stitch defaults to a standard model. The script automatically switches to the most capable model available (model list evolves as Google releases new ones). It opens the model dropdown, scores options by version number + Pro/Thinking labels, and selects the best one.

Stronger model → deeper design reasoning → more nuanced, creative output. Trade-off: ~60-120s vs 30-60s generation time.

Zero API Keys

No API keys. No tokens. No configuration. Stitchflow connects to Google Stitch through your existing Chrome login session via CDP — the same way you'd use Stitch manually in the browser.

File Structure

stitchflow/
├── SKILL.md          # English skill definition (execution guide for AI)
├── SKILL.zh-CN.md    # Chinese skill definition
├── stitch.py         # Core script: CDP launcher + Stitch automation + export
├── icon.png          # Skill icon (1024×1024)
├── demo.mp4          # Full demo video
├── preview.gif       # Animated preview for README
├── README.md         # This file (English)
├── README.zh-CN.md   # Chinese README
└── LICENSE           # MIT

FAQ

Problem Cause Solution
"Stitch iframe not detected" Browser not logged into Google or hasn't visited Stitch Log into Google in Chrome, then open stitch.withgoogle.com once
"CDP connection failed" Chrome not running in CDP mode Run python3 stitch.py --launch-chrome first
"Generate button not found" Stitch UI changed Fixed: home page flow — type prompt, press Enter, auto-creates project
"Generation finished too fast" Prompt didn't inject properly, or false-positive detection Fixed: keyboard input + improved completion detection
"Design looks like a mobile app" Platform selector defaulted to "App" Fixed: script auto-clicks "Web" radio button, verifies with aria-checked

License

MIT © 2026 Leon


Built for the Agent Skills ecosystem — one file, 27+ platforms

About

AI UI design automation: project context → tailored prompt → Google Stitch → screenshot. Cross-platform, agentskills.io compliant, 27+ agent platforms.

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