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 atezer/FMCP --skill generate-figma-screengit clone --depth 1 https://github.com/atezer/FMCPWrote 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/atezer/fmcp/generate-figma-screen)<a href="https://agentmods.dev/skills/atezer/fmcp/generate-figma-screen"><img src="https://agentmods.dev/badge/skills/atezer/fmcp/generate-figma-screen/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/atezer/fmcp/generate-figma-screen"><img src="https://agentmods.dev/badge/skills/atezer/fmcp/generate-figma-screen.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 | $0.00118 | $0.15752 |
| Opus 5.5 | $0.00047 | $0.06301 |
| Sonnet 5.5 | $0.00024 | $0.03150 |
| Haiku 4.5 | $0.00012 | $0.01575 |
Grade A, and why
generate-figma-screen 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 5d 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 — 1,151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate Figma Screen — Kod/Açıklamadan Figma Ekranı
Kullanım (v3.1+):
fmcp-screen-orchestratoraltında, Fast Path match FALSE olduğunda ana üretim motoru. Doğrudan entry point DEĞİL. Kullanıcı "ekran üret" dediğinde önce orchestrator yüklenir; orchestrator Fast Path match yapamadıysa buraya düşer.
Design Token Kuralı: Bu skill'deki kod örneklerinde geçen font adları, renk kodları, piksel boyutları yalnızca FORMAT gösterimidir. Çalışma anında tüm design token değerleri (font, renk, boyut, spacing, radius, gölge) kayıtlı kütüphaneden (
figma_get_variables,figma_get_styles) veya kullanıcıdan okunmalıdır. Hardcoded token değeri kullanma. Detay:project-context.md→ "Design Token Kuralı".
Overview
Bu skill, bir kod tabanından veya metin açıklamasından Figma'da tam sayfa/ekran oluşturur. Temel ilke: hardcode hex renk ve piksel değerleri yerine yayınlanmış design system bileşenlerini (component instance), değişkenlerini (variable) ve stillerini (text/effect style) kullanmak.
Topluluk figma-generate-design skill'inden uyarlanmış, F-MCP Bridge araçlarına göre yeniden yazılmıştır.
Zorunlu: Her figma_execute çağrısından önce figma-canvas-ops kılavuzundaki kuralları uygula.
Skill Boundaries
- Bu skill: Figma'da ekran oluşturma/güncelleme (DS bileşen instance'ları ile)
- Figma'dan kod üretmek istiyorsan → implement-design
- Yeniden kullanılabilir bileşen/variant oluşturmak istiyorsan → generate-figma-library
- Code Connect eşlemesi istiyorsan → code-design-mapper
Prerequisites
- F-MCP Bridge plugin bağlı olmalı
- Hedef Figma dosyasında yayınlanmış DS bileşenleri (veya team library erişimi) olmalı
- Kaynak: kod dosyaları veya ekran açıklaması
F-MCP skill koordinasyonu
- Önce (isteğe bağlı):
audit-figma-design-systemile mevcut ekranın DS uyumunu kontrol et - Birlikte:
figma-canvas-ops(herfigma_executeöncesi zorunlu) - Sonra:
figma-a11y-auditile erişilebilirlik kontrolü;design-drift-detectorile kod parity'si
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.
- 5d ago Changed ba8c7b693043
- 1mo ago First seen · 1,151 lines · 118 tokens per session scan A 39bc366bb7af
generate-figma-screen is a skill published in the GitHub repository atezer/FMCP (10 stars, last pushed 5d ago), licensed MIT. It adds 118 tokens to every session and 15,752 once invoked, about $0.0005 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
theme-audit
Audit theme parity: tokens missing or unchanged per theme, component tokens bypassing semantics, contrast within each theme, resolver contexts, theme-switch regressions. Triggers: dark mode audit, theme coverage, brand variant parity. For general token structure use token-audit.
token-audit
Audit how design tokens are defined: tiers, naming, alias chains, raw values, orphans, DTCG readiness. Triggers: audit my tokens, token architecture review, token health check. Not for code consuming tokens (token-compliance), theme parity (theme-audit) or Figma variables (figma-variable-audit).
accessibility-per-component
Audit one design system component's accessibility against WCAG 2.2 AA: keyboard, screen reader, contrast, focus, ARIA, target size. Trigger: a11y audit, is this accessible, WCAG check, screen reader support, keyboard navigation check. Not for page- or product-wide audits.
ai-component-description
Write a six-section prose description (purpose, props, anti-patterns, composition, accessibility, examples) for a Figma component's description field so LLMs read it via MCP. Triggers: describe this component for AI, Figma MCP description. JSON metadata files: use metadata-schema-generator.
codebase-index
Generate machine-readable index files in .ai/index/ (component inventory, uses/usedBy graph, stats) for AI agents. Triggers: index my codebase, build a relationship graph, what depends on what. Not an assessment; for library health use component-audit.
component-decision-tree
Write "choosing between" pages (docs/choosing/) that route an intent to the right component via narrowing questions; YAML trees on request. Triggers: which component should I use, choose between X and Y, dialog vs drawer, selection guide. One chosen component: usage-guidelines.