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 supercharge-growth/ai-design-skills --skill figma-to-tailwind-by-strangergit clone --depth 1 https://github.com/supercharge-growth/ai-design-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/supercharge-growth/ai-design-skills/figma-to-tailwind-by-stranger)<a href="https://agentmods.dev/skills/supercharge-growth/ai-design-skills/figma-to-tailwind-by-stranger"><img src="https://agentmods.dev/badge/skills/supercharge-growth/ai-design-skills/figma-to-tailwind-by-stranger/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/supercharge-growth/ai-design-skills/figma-to-tailwind-by-stranger"><img src="https://agentmods.dev/badge/skills/supercharge-growth/ai-design-skills/figma-to-tailwind-by-stranger.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 | $0.00072 | $0.00864 |
| Opus 5 | $0.00036 | $0.00432 |
| Sonnet 5 | $0.00014 | $0.00173 |
| Haiku 4.5 | $0.00007 | $0.00086 |
Grade A, and why
figma-to-tailwind-by-stranger 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Figma to Tailwind
Generates a clean, responsive React component from a Figma frame. Reuses tokens from the project (tokens.json, tailwind.config.*, or existing components) rather than dumping hex values inline.
When to use
- "Build this Figma frame as a React component"
- "Turn this design into code"
- "Make a responsive Tailwind version of this"
- After tokens have been extracted via design-token-extractor
When NOT to use
- The user wants a quick visual mockup, not production code (use an artifact instead)
- The codebase uses a different styling system (CSS modules, styled-components, vanilla CSS) — adapt manually
- Pixel-perfect static reproduction is required and tokens don't exist yet — extract tokens first
Inputs
- A Figma frame URL or selection (via Figma MCP if connected, otherwise a screenshot + a description)
- The project root, so the skill can find
tailwind.config,tokens.json, or existing component patterns
Steps
- Read the design. Pull frame data via the Figma MCP if available; otherwise inspect the screenshot.
- Map to tokens. For every color, font size, spacing, and radius — find the matching token in the project. If no match exists, flag it (don't silently hardcode).
- Detect breakpoints. If the design includes mobile/tablet/desktop frames, infer
sm:/md:/lg:variants. Otherwise design mobile-first and note assumptions. - Identify reusable pieces. If the frame contains a card, badge, button, or input that already exists in the codebase — import it instead of re-implementing.
- Generate the component. Functional component, named export, TypeScript if the project uses it. Props for any obvious variant (size, intent, disabled state).
- Add a usage example in a comment at the top.
- Print a checklist of: tokens used, tokens missing, components reused, things to verify with the designer.
Output format
A single .tsx (or .jsx) file ready to drop into the project, plus a short summary in chat:
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.
- 12d ago First seen · 77 lines · 72 tokens per session scan A 7a4b31ef08fa
figma-to-tailwind-by-stranger is a skill published in the GitHub repository supercharge-growth/ai-design-skills (2 stars, last pushed 3mo ago), licensed MIT. It adds 72 tokens to every session and 864 once invoked, about $0.0004 per session on Opus 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 2026-08-31.
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