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Agent Skill · 效率

figma-to-mobile(Figma TO mobile 浏览器)

用于辅助界面设计、视觉规范、排版、配色、布局和交互体验优化。它适合让 Agent 根据产品场景整理页面结构、生成 UI 方案、检查视觉一致性或改进组件层级。使用时需要结合现有品牌、设计系统和用户任务,不应只堆装饰元素;涉及真实页面改动时,应通过截图或浏览器预览检查文本溢出、对齐和响应式表现。

figma-to-mobile 是效率类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描有提醒项,按安装量在效率类的 21,003 个 Skill 里排第 10,572。

总安装 5,092周安装 204GitHub Stars 公开资料未说明下载 1,648核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.3.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:figma-to-mobile(Figma TO mobile 浏览器)
来源仓库:https://github.com/timeaground/figma-to-mobile
安装命令:
openclaw skills install figma-to-mobile
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install figma-to-mobile

这个 Skill 是做什么的

效率类 Skill 把重复的整理、汇总、转换工作交给助手完成,减少手工复制粘贴。

将 Figma 设计转换为移动端原生代码的转换工具。支持 Android(Jetpack Compose/ XML)和 iOS(SwiftUI/ UIKit)。提供跨平台 UI 自动生成能力。安装命令:openclaw skills install figma-to-mobile。

需用户提供 Figma 链接并明确目标平台要求。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install figma-to-mobile;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

figma-to-mobile 怎么安装?

在终端执行 openclaw skills install figma-to-mobile。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

figma-to-mobile 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

figma-to-mobile 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

figma-to-mobile 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

figma-to-mobile 用的人多吗?

公开数据是累计安装 5,092 次,近一周安装 204 次,下载 1,648 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

figma-to-mobile 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理效率类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

效率类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
github

GitHub 代码协作 · OpenClaw

7,632,918545需要联网MIT-0通过
nano-pdf

Nano PDF 文档 · OpenClaw

4,249,476231需要联网MIT-0通过
auto-updater

自动更新程序 · OpenClaw

2,964,063386操作浏览器MIT-0通过
video-frames

视频帧 · OpenClaw

2,621,304112需要联网MIT-0通过
gemini

Gemini 助手 · OpenClaw

2,547,39648需要联网MIT-0有提醒
figma-to-mobile

Figma TO mobile 浏览器 · 本页

5,092—接触敏感数据MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
figma-to-mobile
description
>
metadata

Figma to Mobile

Convert Figma designs to mobile UI code with interactive clarification.

Supported: Android Compose, Android XML, iOS SwiftUI, iOS UIKit.

Prerequisites

  • FIGMA_TOKEN environment variable set (Figma > Settings > Personal Access Tokens)
  • Python 3.8+ with requests package

Trigger & Input

This skill activates when a user provides a Figma link.

The user may also include inline hints alongside the link, such as:

  • Target platform: "Android XML", "Compose", "SwiftUI", "UIKit"
  • Layout preferences: "use ConstraintLayout", "prefer StackView"
  • Component notes: "the switch is our custom CompactSwitch", "this is a dynamic list"
  • Any other context about the design

If the user provides hints, respect them and skip the corresponding questions. For example, if the user says "Android XML, the 3 cards are a RecyclerView list", do NOT ask about output format or whether the cards are dynamic/static.

Workflow

Step 1: Fetch & Analyze

When user provides Figma link(s):

  1. Determine the input type:

A. Link without specific node-id (no node-id, or node-id=0-1): This link points to the entire page, not a specific frame. Tell the user: > This link points to the whole page. Please select the frame you want in Figma, right-click it, and choose "Copy link to selection", then send that link. > If you want to convert multiple frames, send multiple links.

B. Single frame link (has specific node-id): Run scripts/figma_fetch.py "<url>" → returns that frame's design data. Proceed to analysis.

C. Multiple links (user sends 2+ URLs): First, determine the relationship by examining frame names and user context:

- Same page, different visual states (e.g. "首页-有banner" and "首页-无banner"): Use --compare mode to fetch all and get a diff summary. Generate multi-state code (conditional visibility, state switching).

- Parent page + overlay/drawer (e.g. "首页" + "首页-抽屉-xxx"): Generate each as an independent layout file. Then tell the user the relationship: > Frame 1 ("首页") and Frame 2 ("首页-抽屉") look like a main page + side drawer. > I've generated two separate layout files. How you wire them together (DrawerLayout, Navigation, etc.) depends on your project architecture.

The Skill's job is generating UI layout code, not deciding architecture (Activity vs Fragment vs Navigation).

- Different independent pages (e.g. "首页" + "设置页" + "个人中心"): Process each independently. Fetch them one at a time with a pause between requests to avoid rate limiting. Present a summary of all pages, then ask which to convert first (or convert all sequentially).

- Not sure: Ask the user — "These frames look related but I'm not sure how. Are they different states of the same page, a page with an overlay, or independent pages?"

Rate limit protection for multiple links: When fetching multiple nodes, wait 2-3 seconds between requests. Never fire more than 2 requests in parallel.

  1. If the link has no specific node-id, ask the user to re-copy from the specific frame (see A above). Do NOT call the API.
  1. Analyze the structure: identify sections, repeated patterns, component types
  2. Note INSTANCE nodes — they indicate reusable components. Check variantProperties for component state (e.g. State=Default, Size=Large) — these map to multi-state code
  3. Note gradient/shadow data — flag for the user if complex
  4. Apply Figma node interpretation rules before generating code

Detailed interpretation rules: Read references/figma-interpretation.md

Step 1.5: Structure Summary

Before asking any questions, present a brief structure summary to the user so they can confirm your understanding:

I see: [navigation bar with back button + title] → [2 content sections: user profile card, settings list (8 items)] → [bottom action button]. Total ~25 nodes.

Keep it to 2-3 lines. Mention:

  • Major sections identified (nav bar, content areas, footer)
  • Repeated patterns ("8 similar list items", "3 tab labels")
  • Notable elements (gradients, complex illustrations, stacked cards)

If the user says "that's wrong" or corrects the structure, adjust understanding before proceeding to Step 2.

If the structure is simple and obvious (e.g., a single card with a few text fields), skip this step.

Step 2: Confirm & Clarify

Question priority (strict order — ask earlier questions first):

  1. Output format (MUST ask first unless user already specified)

→ Android XML / Compose / SwiftUI / UIKit This determines all subsequent analysis phrasing and code output.

  1. Structural ambiguities (only ask what you're genuinely unsure about)

→ "These N items look similar — dynamic list or fixed layout?" → "This area: single image asset or icon-on-background combo?"

  1. Component choices (only if platform-relevant)

→ "Any custom components to use? (otherwise I'll use platform defaults)"

Rules for questions:

  • Skip any question the user already answered via inline hints
  • Max 3-5 questions total, fewer is better
  • Each question gives concrete options with one-line pros/cons
  • Every question includes an open option: "or tell me more about this"
  • Use natural language, no JSON or technical dumps
  • If everything is clear (user gave full context + simple structure), skip Step 2 entirely

Confidence guide — when to ask vs. when to just generate:

  • ≥3 sibling nodes with similar structure → likely a list → ASK (dynamic vs static)
  • INSTANCE nodes sharing same componentId → reusable component → MENTION but can default
  • Single clear hierarchy, no ambiguity → high confidence → SKIP questions, go to Step 3
  • Gradient/complex shadow in design → MENTION in summary ("I see a gradient here, I'll approximate it as X")

Step 2.5: Project Scan (optional but recommended)

If the target project is available locally, run a project scan:

python scripts/project_scan.py /path/to/project --json --output scan-report.json

How to use scan results in code generation: Read references/scan-usage.md

Step 3: Generate Code

After user confirms (or if no questions needed), generate code files.

Detailed generation rules: Read references/generation-rules.md

If multiple files are needed, output each with a clear filename header:

📄 activity_notification_settings.xml
[code]

📄 item_expert_notification.xml
[code]

Step 4: Iterate & Capture Feedback

After showing code, ask briefly:

Matches the design? Any adjustments?

The user can then give feedback to refine the output. Common iterations:

  • "间距大了" → adjust specific spacing
  • "Switch 换成我们的 CustomSwitch" → swap component
  • "把标题栏去掉" → remove section
  • "换成 Compose 版本" → regenerate in different format
  • "颜色不对,这里应该是 #333333" → fix specific values

Continue iterating until the user is satisfied. Each round only regenerates the changed parts, not the entire file (unless the user asks for full regeneration).

Feedback capture (automatic): Whenever the user corrects your generated output, log the correction to feedback-log.md in the project root (create if it doesn't exist). Each entry follows this format:

## YYYY-MM-DD HH:MM
- **Platform**: Android XML / Compose / SwiftUI / UIKit
- **Figma node type**: (e.g., FRAME with icon, Tab bar, Button group)
- **Issue**: Brief description of what was wrong
- **Before**: What the agent generated (snippet or description)
- **After**: What the user wanted (snippet or description)
- **Rule candidate**: (optional) If this correction suggests a general pattern rule, note it here

Log entries should be:

  • Concise — only the relevant diff, not entire files
  • Categorized — always include platform and Figma node type for later analysis
  • Actionable — focus on the mapping error, not cosmetic preferences (e.g., "user prefers 16dp" is not a rule; "VECTOR compositions should be single ImageView" is)

Do NOT log:

  • One-off personal preferences (specific color choices, naming conventions)
  • Corrections to non-mapping issues (typos, import statements)
  • Feedback the user explicitly says is project-specific, not general

Periodically (or when asked), run scripts/feedback_analyze.py to identify patterns and generate rule candidates.

Error Handling

  • FIGMA_TOKEN not set (script outputs FIGMA_TOKEN_NOT_SET) → do NOT ask user to run commands. Instead:

1. Tell the user you need a Figma Personal Access Token 2. Tell them where to get it: Figma → avatar (top-left) → Settings → Security → Personal Access Tokens 3. Ask them to paste the token in chat 4. Once they provide it (starts with figd_), write it to the project root .env file: echo 'FIGMA_TOKEN=figd_xxx' >> .env 5. Retry the figma_fetch command — it will read from .env automatically

  • FIGMA_TOKEN invalid (API returns 403/401) → token may have expired or been revoked. Ask user to regenerate and paste new token. Update .env file.
  • Invalid URL → show valid URL example: https://www.figma.com/design/<fileKey>/<name>?node-id=<id>
  • API error → show error message, suggest checking network/proxy
  • Node too large (>200 children) → suggest selecting a smaller frame
  • Depth auto-increased → the script auto-retries with deeper depth if it detects truncated children. Inform user if this happens ("I needed to fetch deeper to get all details").

平台分布

OpenClaw

83.16%
按下载量换算1,370

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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