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 SummerSec/SumSec-Skills --skill stitch-skillgit clone --depth 1 https://github.com/SummerSec/SumSec-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/summersec/sumsec-skills/stitch-skill)<a href="https://agentmods.dev/skills/summersec/sumsec-skills/stitch-skill"><img src="https://agentmods.dev/badge/skills/summersec/sumsec-skills/stitch-skill/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/skills/summersec/sumsec-skills/stitch-skill"><img src="https://agentmods.dev/badge/skills/summersec/sumsec-skills/stitch-skill.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 | $0.00050 | $0.02741 |
| Opus 5.5 | $0.00020 | $0.01096 |
| Sonnet 5.5 | $0.00010 | $0.00548 |
| Haiku 4.5 | $0.00005 | $0.00274 |
Grade A, and why
stitch-design-taste 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.
This is a copy
100% identical to stitch-design-taste — 0 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 — 185 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/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: Variance 8, Motion 6, Density 4. 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.
- 1mo ago First seen · 185 lines · 50 tokens per session scan A 46bdb08fee2d
stitch-design-taste is a skill published in the GitHub repository SummerSec/SumSec-Skills (8 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 50 tokens to every session and 2,741 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to stitch-design-taste, differing in 0 lines, and is treated as a copy.
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