Borrowing it
Nothing to install: this file belongs to felixAnhalt/figma-to-code-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/felixAnhalt/figma-to-code-mcp/main/.opencode/skills/figma-token-extraction/SKILL.mdgit clone --depth 1 https://github.com/felixAnhalt/figma-to-code-mcpWrote 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/felixanhalt/figma-to-code-mcp/figma-token-extraction)<a href="https://agentmods.dev/skills/felixanhalt/figma-to-code-mcp/figma-token-extraction"><img src="https://agentmods.dev/badge/skills/felixanhalt/figma-to-code-mcp/figma-token-extraction/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/felixanhalt/figma-to-code-mcp/figma-token-extraction"><img src="https://agentmods.dev/badge/skills/felixanhalt/figma-to-code-mcp/figma-token-extraction.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 | $0.00025 | $0.00472 |
| Opus 5.5 | $0.00010 | $0.00189 |
| Sonnet 5.5 | $0.00005 | $0.00094 |
| Haiku 4.5 | $0.00003 | $0.00047 |
Grade A, and why
figma-token-extraction 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 2mo 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.
What it actually says
What I do
I know the full design token extraction pipeline in src/figma/tokenizer/.
Pipeline (in extractTokens() at src/figma/tokenizer/index.ts)
Step 1: Collect Figma variable refs
collectFigmaVarRefs() walks root + componentSets gathering _varRefs sidecars from Style and Layout objects. First-encountered name wins.
Step 2: Count frequencies
countFrequencies() (in frequencies.ts) tallies colors, spacings, radii, shadows, typographies, padding combos, heights. Var-bound values are skipped.
Step 3: Build semantic registries
buildSemanticTokenRegistry() (in registry.ts) assigns semantic names from frequency-ordered data. Categories:
- Colors →
COLOR_SEMANTIC_NAMES(primary, secondary, background, text, border, ...) - Shadows →
SHADOW_SEMANTIC_NAMES(card, dropdown, modal, ...) - Spacings → auto-generated (spacingXs, spacingSm, ...)
- Radii → auto-generated (radiusSm, radiusMd, ...)
- Typographies → auto-generated (headingXl, body, caption, ...)
- Padding combos →
PADDING_COMBO_SEMANTIC_NAMES - Heights → auto-generated (heightSm, heightMd, ...)
Step 4: Build tokens registry
Merges invented tokens with Figma variable entries. Multiple Figma variables → same raw value → kept distinct.
Step 5: Replace raw values with token refs
replaceNodeTokens() and replaceComponentSetTokens() (in replace/) swap raw rgba/dimensions for { token: "category.name" } references.
Step 6: Strip _varRefs
stripVarRefsFromResponse() removes all _varRefs sidecars — must not appear in final output.
When to use me
Use this when:
- Adding a new token category
- Debugging token assignment
- Understanding why a value got a particular semantic name
- Modifying the tokenizer pipeline
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.
- 2mo ago First seen · 52 lines · 25 tokens per session scan A eaa9620fce6e
figma-token-extraction is a skill published in the GitHub repository felixAnhalt/figma-to-code-mcp (7 stars, last pushed yesterday), licensed MIT. It adds 25 tokens to every session and 472 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other skills, from other repositories
webgl-holographic-foil
A self-contained WebGL2 hero: thin-film interference over a crushed-foil surface whose palette shifts with the viewing angle; move the cursor to tilt the film.
html-ppt-hermes-cyber-terminal
OpenDesign + BYOK: choosing and wiring your own model, hands-on — cost, quality, and the routing decision. Built as a decision-grade AI literacy deck for engineers, IT, applied-AI teams.
html-ppt-taste-brutalist
16:9 HTML deck in tactical-telemetry / CRT-terminal taste. Deactivated-CRT charcoal slides, white-phosphor monospace, hazard-red accent, scanline overlay, ASCII syntax, density over decoration. Distilled from Leonxlnx/taste-skill brutalist-skill (Tactical Telemetry mode).
visual-ralph
Visual Ralph orchestration for frontend UI from generated references, static references, or live URL targets, using $ultragoal with built-in visual verdict and pixel-diff evidence until the implementation matches and leaves a reproducible design system.
glance-canonical-layouts
Use this skill to create home screen widgets using Jetpack Glance Canonical Layouts from the Android Platform Samples project, or when asked to implement standard widget layout patterns (including Check List, Image Grid, Snap Scrolling, and Standard Toolbar).
accessibility
Consolidated accessibility skill entrypoint for WCAG 2.2, ARIA Authoring Practices, cognitive accessibility, Section 508, EN 301 549, design intent verification, and the Accessibility Planner workflow.