Stitch Design Skills is a collection of Agent Skills and plugins for Google Stitch, a design tool accessed through the Stitch MCP server. It is for coding agents such as Codex, Antigravity, Gemini CLI, Claude Code, Cursor, and OpenCode, with catalogue entries covering Stitch design, build, and utility workflows.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add google-labs-code/stitch-skills --skill taste-designgit clone --depth 1 https://github.com/google-labs-code/stitch-skillsWrote 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/skills/google-labs-code/stitch-skills/taste-design)<a href="https://agentmods.dev/skills/google-labs-code/stitch-skills/taste-design"><img src="https://agentmods.dev/badge/skills/google-labs-code/stitch-skills/taste-design.svg" alt="Measured on agentmods" height="20"></a>- Socket pass
- Snyk pass
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 | $0.00047 | $0.02925 |
| Opus 5 | $0.00023 | $0.01463 |
| Sonnet 5 | $0.00009 | $0.00585 |
| Haiku 4.5 | $0.00005 | $0.00293 |
Grade A, and why
taste-design 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 9d 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.
This is a copy
88% identical to stitch-design-taste — 13 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Stitch Design Taste — Semantic Design System Skill
Overview
This skill generates DESIGN.md files optimized for Google Stitch screen generation. It translates the battle-tested anti-slop frontend engineering directives into Stitch's native semantic design language — descriptive, natural-language rules paired with precise values that Stitch's AI agent can interpret to produce premium, non-generic interfaces.
The generated DESIGN.md serves as the single source of truth for prompting Stitch to generate new screens that align with a curated, high-agency design language. Stitch interprets design through "Visual Descriptions" supported by specific color values, typography specs, and component behaviors.
Prerequisites
- Access to Google Stitch via labs.google.com/stitch
- Optionally: Stitch MCP Server for programmatic integration with Cursor, Antigravity, or Gemini CLI
The Goal
Generate a DESIGN.md file that encodes:
- Visual atmosphere — the mood, density, and design philosophy
- Color calibration — neutrals, accents, and banned patterns with hex codes
- Typographic architecture — font stacks, scale hierarchy, and anti-patterns
- Component behaviors — buttons, cards, inputs with interaction states
- Layout principles — grid systems, spacing philosophy, responsive strategy
- Motion philosophy — animation engine specs, spring physics, perpetual micro-interactions
- Anti-patterns — explicit list of banned AI design clichés
Analysis & Synthesis Instructions
1. Define the Atmosphere
Evaluate the target project's intent. Use evocative adjectives from the taste spectrum:
- Density: "Art Gallery Airy" (1–3) → "Daily App Balanced" (4–7) → "Cockpit Dense" (8–10)
- Variance: "Predictable Symmetric" (1–3) → "Offset Asymmetric" (4–7) → "Artsy Chaotic" (8–10)
- Motion: "Static Restrained" (1–3) → "Fluid CSS" (4–7) → "Cinematic Choreography" (8–10)
Default baseline: Creativity 9, Variance 8, Motion 6, Density 5. Adapt dynamically based on user's vibe description.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 192 lines · 47 tokens per session scan A e425fdb7ab25
taste-design is a skill published in the GitHub repository google-labs-code/stitch-skills (8,270 stars, last pushed 21d ago), licensed Apache-2.0. It adds 47 tokens to every session and 2,925 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to stitch-design-taste, differing in 13 lines, and is treated as a copy.
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