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 | $0.00013 | $0.00236 |
| Sonnet 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 10d 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.
- 10d 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 (5 stars, last pushed 13d ago), licensed MIT. It adds 25 tokens to every session and 472 once invoked, about $0.0001 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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