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Agent Skill · 研究检索

design-screenshot(设计截图)

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。

design-screenshot 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 43,020。

总安装 1,022周安装 43GitHub Stars 6下载 358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
unknown

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:design-screenshot(设计截图)
来源仓库:https://github.com/duc01226/easyplatform
仓库路径:skills/design-screenshot
安装命令:
npx skills add https://github.com/duc01226/easyplatform --skill design-screenshot
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/duc01226/easyplatform --skill design-screenshot

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

基于截图与设计稿生成结构化 UI 规范文档,支持组件状态与 Token 提取。适合逆向工程现有界面或从 Figma 导出生成开发可用 JSON 规格。采用任务拆分机制防止上下文丢失,确保复杂分析过程的可追溯性。安装需通过 npx 添加指定 GitHub 仓库,依赖图像识别与结构化解析能力。

design-screenshot 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/design-screenshot

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 Codex、Claude、Cursor、Gemini CLI;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 npx skills add https://github.com/duc01226/easyplatform --skill design-screensho…;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

    它需要需要联网,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

design-screenshot 怎么安装?

在终端执行 npx skills add https://github.com/duc01226/easyplatform --skill design-screenshot。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

design-screenshot 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。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。

design-screenshot 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

design-screenshot 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

design-screenshot 用的人多吗?

公开数据是累计安装 1,022 次,近一周安装 43 次,下载 358 次,GitHub 6 星。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。

design-screenshot 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

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
design-screenshot

设计截图 · 本页

1,0226需要联网未明确有提醒

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

[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.
Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.
AI Mistake Prevention — Failure modes to avoid on every task: - Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal. - Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing. - Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain. - Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path. - When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site. - Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code. - Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks. - Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis. - Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly. - Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.

Think hard to plan & start designing follow exactly this screenshot: $ARGUMENTS

Skill Variant: Variant of design skills — recreate/implement from screenshot.

Quick Summary

Goal: Analyze a screenshot and recreate the design as functional code.

Workflow:

  1. Analyze — Process screenshot with vision capabilities
  2. Research — Run ui-ux-pro-max for matching design patterns
  3. Implement — Recreate the design as code using design subagent

Key Rules:

  • Always activate ui-ux-pro-max FIRST for design intelligence
  • Match the screenshot as closely as possible
  • Use ai-multimodal for detailed screenshot analysis

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

Required Skills (Priority Order)

  1. ui-ux-pro-max - Design intelligence database (ALWAYS ACTIVATE FIRST)
  2. frontend-design - Screenshot analysis and replication

Ensure token efficiency while maintaining high quality.

Workflow:

  1. Use ai-multimodal skills to describe super details of the screenshot (design style, trends, fonts, colors, border, spacing, elements' positions, size, shape, texture, material, light, shadow, reflection, refraction, blur, glow, image, background transparency, transition, etc.)

- IMPORTANT: Try to predict the font name (Google Fonts) and font size in the given screenshot, don't just use Inter or Poppins.

  1. Use ui-ux-designer subagent to create a design plan following the progressive disclosure structure so the final result matches the screenshot:

- Create a directory using naming pattern from ## Naming section. - Save the overview access point at plan.md, keep it generic, under 80 lines, and list each phase with status/progress and links. - For each phase, add phase-XX-phase-name.md files containing sections (Context links, Overview with date/priority/statuses, Key Insights, Requirements, Architecture, Related code files, Implementation Steps, Todo list, Success Criteria, Risk Assessment, Security Considerations, Next steps). - Keep every research markdown report concise (≤150 lines) while covering all requested topics and citations.

  1. Then implement the plan step by step.
  2. If user doesn't specify, create the design in pure HTML/CSS/JS.
  3. Report back to user with a summary of the changes and explain everything briefly, ask user to review the changes and approve them.
  4. If user approves the changes, update the ./docs/design-guidelines.md docs if needed.

Important Notes:

  • ALWAYS REMEBER that you have the skills of a top-tier UI/UX Designer who won a lot of awards on Dribbble, Behance, Awwwards, Mobbin, TheFWA.
  • Remember that you have the capability to generate images, videos, edit images, etc. with ai-multimodal skill for image generation. Use them to create the design with real assets.
  • Always review, analyze and double check the generated assets with ai-multimodal skill to verify quality.
  • Use media-processing skill (RMBG) to remove background from generated assets if needed.
  • Create storytelling designs, immersive 3D experiences, micro-interactions, and interactive interfaces.
  • Maintain and update ./docs/design-guidelines.md docs if needed.

Closing Reminders

  • MANDATORY IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting
  • MANDATORY IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code
  • MANDATORY IMPORTANT MUST ATTENTION cite file:line evidence for every claim (confidence >80% to act)
  • MANDATORY IMPORTANT MUST ATTENTION add a final review todo task to verify work quality
  • MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.
  • MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.

[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using TaskCreate.

平台分布

Codex

37.48%
按下载量换算134

Claude

29.46%
按下载量换算105

Cursor

18.07%
按下载量换算65

Gemini CLI

10.18%
按下载量换算36

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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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