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 seaworld008/Commonly-used-high-value-skills --skill figmagit clone --depth 1 https://github.com/seaworld008/Commonly-used-high-value-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/seaworld008/commonly-used-high-value-skills/figma)<a href="https://agentmods.dev/skills/seaworld008/commonly-used-high-value-skills/figma"><img src="https://agentmods.dev/badge/skills/seaworld008/commonly-used-high-value-skills/figma/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/seaworld008/commonly-used-high-value-skills/figma"><img src="https://agentmods.dev/badge/skills/seaworld008/commonly-used-high-value-skills/figma.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 117 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00032 | $0.01878 |
| Opus 5.5 | $0.00013 | $0.00751 |
| Sonnet 5.5 | $0.00006 | $0.00376 |
| Haiku 4.5 | $0.00003 | $0.00188 |
Grade A, and why
figma 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 1mo 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 — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Figma MCP (Design-to-Code)
Figma MCP 是连接设计稿与生产代码的超级引擎。它通过 Figma API 获取结构化设计上下文、变量定义及原始素材,并结合大模型的推理能力,将视觉稿一键转化为符合项目规范的 React/Tailwind/Vue 代码。
安装与前提条件
# 确保已安装 Figma MCP Server
mcp_call({ action: "search", keyword: "figma" });
# 获取访问令牌 (PAT)
# 详见 references/figma-mcp-config.md
Figma MCP 核心集成流程 (Workflow)
为了确保 1:1 的视觉还原度和高性能的代码实现,必须严格遵循以下流程:
- 获取设计上下文 (get_design_context):首先获取目标 Node ID 的结构化 JSON 表示,理解其层级、间距、填充和排版属性。
- 处理大数据量 (Metadata First):如果 Node 层级过深,先运行
get_metadata获取高层级节点地图,再精准抓取需要的子节点。 - 视觉对齐 (get_screenshot):运行
get_screenshot获取节点的实时渲染图片,作为实现时的绝对参考。 - 素材下载 (Asset Acquisition):在开始编码前,下载所有图标(Icons)和装饰图(Images)。
- 规范化翻译 (Code Translation):将 Figma 的属性(如
cornerRadius: 8)映射到项目的 Design Tokens(如rounded-lg)。 - 最终验证 (Visual Regression):完成开发后,再次对比 Figma 截图,确保 1:1 还原。
触发条件 / When to Use
- 新功能 UI 开发:用户给出一个 Figma 链接,要求实现对应的组件或页面。
- UI 细节优化:针对现有页面进行微调,以对齐设计稿的最新改动。
- 设计规范审计 (Design Audit):自动提取 Figma 里的 Color Palette 或 Typography 并与代码库中的
tailwind.config.js对比。 - 图标与静态资源同步:需要批量导出 SVG 图标并转换为 React 组件。
- 响应式布局实现:需要查看不同 Breakpoints(Desktop, Tablet, Mobile)下的设计差异。
核心能力 / Core Capabilities
1. 结构化设计解析 (Structural Parsing)
- 操作步骤:
- 调用
mcp_call({ name: "get_design_context", arguments: { fileKey, nodeIds } })。 - 解析
children数组,识别TEXT,VECTOR,INSTANCE等节点类型。 - 自动计算 Auto-layout 属性(Gap, Padding, Alignment)。
- 调用
- 最佳实践:如果发现节点名称是“Frame 1234”,主动询问设计人员其真实的语义名称(如“Primary Button”)。
2. 图像与变量提取 (Variable Extraction)
- 操作步骤:
- 检索 Figma Variables 和 Styles。
- 将十六进制颜色码转换为项目使用的命名变量(如
#3B82F6->brand-primary)。 - 通过
get_file_variables获取全局主题定义。
- 最佳实践:优先使用
variable-id而非硬编码颜色。
3. 视觉引导编码 (Vision-guided Coding)
- 操作步骤:
- 在编写 CSS/Tailwind 时,将
get_screenshot的结果传入多模态模型进行视觉校验。 - 捕捉微小的阴影(Box-shadow)和渐变(Gradient)细节。
- 在编写 CSS/Tailwind 时,将
- 最佳实践:使用
image_edit技能在截图上标注出具体的像素间距,辅助编码。
4. 资产自动化处理 (Asset Handling)
- 操作步骤:
- 检测 Figma 返回的 localhost 素材源。
- 自动将其下载并命名为合规的格式(如
icon-user-profile.svg)。 - 如果是 SVG,自动通过
svgr转化为 React 组件。
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago Changed · -27 tokens per session 5945caec2c3f
- 1mo ago First seen · 131 lines · 59 tokens per session scan A 86867fb69dab
figma is a skill published in the GitHub repository seaworld008/Commonly-used-high-value-skills (73 stars, last pushed today), licensed MIT. It adds 32 tokens to every session and 1,878 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 2026-09-03.
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