agentleFS
harrychuangharrychuang/cursor-skills/figma-componentize/SKILL.md

figma-componentize

Skill19 starsChanged 5 months agoNo licenceView on GitHub

Turn raw (non-component) UI in a Figma design into components: detect which UI in a section, frame, or single element is not built from components, group it into components, variants (Style, Size, State), and component properties, build them bottom-up on the Components page, tokenize them via figma-m3-variables Workflow F (color, typography, radius, spacing, elevation), then replace the originals with instances and prove the look is unchanged. Optional design system document page: all local tokens and components. Use when: a designer shares a section, frame, or element link and asks to componentize it, create components from it, or replace raw layers with instances. Token-only requests (hardcoded values to Variables, no components) go to figma-m3-variables. Triggers: componentize, make components, create components from design, convert to component, detect components, replace with instances, component set, variants, 元件化, 建立元件, 做成元件, 轉成元件, 還不是元件, 拆成元件, 換成 instance, 建立 variants, design system document, 設計系統文件.

The file

Show its rules and text

We split this skill into the rules it gives an agent

24 rules. About 0 are common, 14 are distinctive, and 10 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈14

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 10

    Very specific

    Tied to their project's names, files or tools. Probably skip.

No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.