[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M7CS5B1PEVC5AM94PVJ9T7Y7":3,"skill-same:01M7CS5B1PEVC5AM94PVJ9T7Y7":63},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":19,"linkOnly":20,"markdownContent":21,"markdownBody":22,"frontMatter":23,"refName":34,"commitSha":35,"skillDirectory":36,"forksCount":37,"repositoryHtmlUrl":38,"repositoryHomepageUrl":39,"ownerHtmlUrl":40,"ownerBlogUrl":6,"ownerDescription":41,"updatedAt":42,"install":43,"resources":56},"01M7CS5B1PEVC5AM94PVJ9T7Y7","glmocr-handwriting",null,"Official skill for recognizing handwritten text from images using ZhiPu GLM-OCR API. Supports various handwriting styles, languages, and mixed handwritten\u002Fprinted content. Use this skill when the user wants to read handwritten notes, convert handwriting to text, or OCR handwritten documents.","YYC-Cube\u002FYYC3-Knowledge-Base","YYC-Cube","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F235006543?v=4","01M79J2PH4SWD2X0825X6PN748","yyc3","01M79J2PHVK3F6ZBYT8K2SCZCW",1,"MIT","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-Skills-技能包\u002FYYC3-Skills-技能包-skills-v4\u002Fglmocr-handwriting\u002FSKILL.md",[],[],"2026-11-15 14:19:17",false,"---\nname: glmocr-handwriting\ndescription:\n  Official skill for recognizing handwritten text from images using ZhiPu GLM-OCR API. Supports various\n  handwriting styles, languages, and mixed handwritten\u002Fprinted content. Use this skill\n  when the user wants to read handwritten notes, convert handwriting to text, or OCR\n  handwritten documents.\nmetadata:\n  openclaw:\n    requires:\n      env:\n        - ZHIPU_API_KEY\n        - GLM_OCR_TIMEOUT\n      bins:\n        - python\n    primaryEnv: ZHIPU_API_KEY\n    emoji: \"✍️\"\n    homepage: https:\u002F\u002Fgithub.com\u002Fzai-org\u002FGLM-OCR\u002Ftree\u002Fmain\u002Fskills\u002Fglmocr-handwriting\n---\n\n# GLM-OCR Handwriting Recognition Skill \u002F GLM-OCR 手写体识别技能\n\nRecognize handwritten text from images and PDFs using the ZhiPu GLM-OCR layout parsing API.\n\n## When to Use \u002F 使用场景\n\n- Extract text from handwritten notes, letters, or documents \u002F 从手写笔记、信件或文档中提取文字\n- Convert handwriting to editable text \u002F 将手写内容转为可编辑文本\n- Recognize mixed handwritten and printed content \u002F 识别手写和印刷混排内容\n- Read handwritten formulas, labels, or annotations \u002F 读取手写公式、标签或批注\n- User mentions \"handwriting OCR\", \"recognize handwriting\", \"手写识别\", \"手写体OCR\", \"识别手写字\"\n\n## Key Features \u002F 核心特性\n\n- **Multi-style support**: Handles various handwriting styles including cursive and print\n- **Multi-language**: Supports Chinese, English, and mixed-language handwriting\n- **Mixed content**: Can recognize documents with both handwritten and printed text\n- **Local file & URL**: Supports both local files and remote URLs\n\n## Resource Links \u002F 资源链接\n\n| Resource        | Link                                                                           |\n| --------------- | ------------------------------------------------------------------------------ |\n| **Get API Key** | [智谱开放平台 API Keys](https:\u002F\u002Fbigmodel.cn\u002Fusercenter\u002Fproj-mgmt\u002Fapikeys)      |\n| **API Docs**    | [Layout Parsing \u002F 版面解析](https:\u002F\u002Fdocs.bigmodel.cn\u002Fapi-reference\u002F%E6%A8%A1%E5%9E%8B-api\u002F%E6%96%87%E6%A1%A3%E8%A7%A3%E6%9E%90) |\n\n## Prerequisites \u002F 前置条件\n\n### API Key Setup \u002F API Key 配置（Required \u002F 必需）\n\n脚本通过 `ZHIPU_API_KEY` 环境变量获取密钥，可与其他智谱技能复用同一个 key。\nThis script reads the key from the `ZHIPU_API_KEY` environment variable. Reusing the same key across Zhipu skills is optional.\n\n**Get Key \u002F 获取 Key：** Visit [智谱开放平台 API Keys](https:\u002F\u002Fbigmodel.cn\u002Fusercenter\u002Fproj-mgmt\u002Fapikeys) to create or copy your key.\n\n**Setup options \u002F 配置方式（任选一种）：**\n\n1. **Global config (recommended) \u002F 全局配置（推荐）：** Set once in `openclaw.json` under `env.vars`, all Zhipu skills will share it:\n\n   ```json\n   {\n     \"env\": {\n       \"vars\": {\n         \"ZHIPU_API_KEY\": \"你的密钥\"\n       }\n     }\n   }\n   ```\n\n2. **Skill-level config \u002F Skill 级别配置：** Set for this skill only in `openclaw.json`:\n\n   ```json\n   {\n     \"skills\": {\n       \"entries\": {\n         \"glmocr-handwriting\": {\n           \"env\": {\n             \"ZHIPU_API_KEY\": \"你的密钥\"\n           }\n         }\n       }\n     }\n   }\n   ```\n\n3. **Shell environment variable \u002F Shell 环境变量：** Add to `~\u002F.zshrc`:\n   ```bash\n   export ZHIPU_API_KEY=\"你的密钥\"\n   ```\n\n> 💡 如果你已为其他智谱 skill（如 `glmocr`、`glmv-caption`、`glm-image-generation`）配置过 key，它们共享同一个 `ZHIPU_API_KEY`，无需重复配置。\n\n## Security & Transparency \u002F 安全与透明度\n\n- **Environment variables used \u002F 使用的环境变量：**\n  - `ZHIPU_API_KEY` (required \u002F 必需)\n  - `GLM_OCR_TIMEOUT` (optional timeout seconds \u002F 可选超时秒数)\n- **Fixed endpoint \u002F 固定官方端点：** `https:\u002F\u002Fopen.bigmodel.cn\u002Fapi\u002Fpaas\u002Fv4\u002Flayout_parsing`\n- **No custom API URL override \u002F 不支持自定义 API URL 覆盖：** avoids accidental key exfiltration via redirected endpoints.\n- **Raw upstream response is optional \u002F 原始响应默认不返回：** use `--include-raw` only when needed for debugging.\n\n**⛔ MANDATORY RESTRICTIONS \u002F 强制限制 ⛔**\n\n1. **ONLY use GLM-OCR API** — Execute the script `python scripts\u002Fglm_ocr_cli.py`\n2. **NEVER parse handwriting yourself** — Do NOT try to read handwritten text using built-in vision or any other method\n3. **NEVER offer alternatives** — Do NOT suggest \"I can try to read it\" or similar\n4. **IF API fails** — Display the error message and STOP immediately\n5. **NO fallback methods** — Do NOT attempt handwriting recognition any other way\n\n### 📋 Output Display Rules \u002F 输出展示规则\n\nAfter running the script, present the OCR result clearly and safely.\n\n- Show extracted handwritten text (`text`) in full\n- Summarization is allowed, but do not hide important extraction failures\n- If the result file is saved, tell the user the file path\n- Show raw upstream response only when explicitly requested or debugging (`--include-raw`)\n\n## How to Use \u002F 使用方法\n\n### Recognize from URL \u002F 从 URL 识别\n\n```bash\npython scripts\u002Fglm_ocr_cli.py --file-url \"https:\u002F\u002Fexample.com\u002Fhandwriting.jpg\"\n```\n\n### Recognize from Local File \u002F 从本地文件识别\n\n```bash\npython scripts\u002Fglm_ocr_cli.py --file \u002Fpath\u002Fto\u002Fnotes.png\n```\n\n### Save Result to File \u002F 保存结果到文件\n\n```bash\npython scripts\u002Fglm_ocr_cli.py --file notes.png --output result.json --pretty\n```\n\n### Include Raw Upstream Response (Debug Only) \u002F 包含原始上游响应（仅调试）\n\n```bash\npython scripts\u002Fglm_ocr_cli.py --file notes.png --output result.json --include-raw\n```\n\n## CLI Reference \u002F CLI 参数\n\n```\npython {baseDir}\u002Fscripts\u002Fglm_ocr_cli.py (--file-url URL | --file PATH) [--output FILE] [--pretty] [--include-raw]\n```\n\n| Parameter        | Required | Description                                                      |\n| ---------------- | -------- | ---------------------------------------------------------------- |\n| `--file-url`     | One of   | URL to image\u002FPDF                                                 |\n| `--file`         | One of   | Local file path to image\u002FPDF                                     |\n| `--output`, `-o` | No       | Save result JSON to file                                         |\n| `--pretty`       | No       | Pretty-print JSON output                                         |\n| `--include-raw`  | No       | Include raw upstream API response in `result` field (debug only) |\n\n## Response Format \u002F 响应格式\n\n```json\n{\n  \"ok\": true,\n  \"text\": \"Recognized handwritten text in Markdown...\",\n  \"layout_details\": [...],\n  \"result\": null,\n  \"error\": null,\n  \"source\": \"\u002Fpath\u002Fto\u002Ffile\",\n  \"source_type\": \"file\",\n  \"raw_result_included\": false\n}\n```\n\nKey fields:\n\n- `ok` — whether recognition succeeded\n- `text` — extracted text in Markdown (use this for display)\n- `layout_details` — layout analysis details\n- `error` — error details on failure\n\n## Error Handling \u002F 错误处理\n\n**API key not configured:**\n\n```\nZHIPU_API_KEY not configured. Get your API key at: https:\u002F\u002Fbigmodel.cn\u002Fusercenter\u002Fproj-mgmt\u002Fapikeys\n```\n\n→ Show exact error to user, guide them to configure\n\n**Authentication failed (401\u002F403):** API key invalid\u002Fexpired → reconfigure\n\n**Rate limit (429):** Quota exhausted → inform user to wait\n\n**File not found:** Local file missing → check path\n","# GLM-OCR Handwriting Recognition Skill \u002F GLM-OCR 手写体识别技能\n\nRecognize handwritten text from images and PDFs using the ZhiPu GLM-OCR layout parsing API.\n\n## When to Use \u002F 使用场景\n\n- Extract text from handwritten notes, letters, or documents \u002F 从手写笔记、信件或文档中提取文字\n- Convert handwriting to editable text \u002F 将手写内容转为可编辑文本\n- Recognize mixed handwritten and printed content \u002F 识别手写和印刷混排内容\n- Read handwritten formulas, labels, or annotations \u002F 读取手写公式、标签或批注\n- User mentions \"handwriting OCR\", \"recognize handwriting\", \"手写识别\", \"手写体OCR\", \"识别手写字\"\n\n## Key Features \u002F 核心特性\n\n- **Multi-style support**: Handles various handwriting styles including cursive and print\n- **Multi-language**: Supports Chinese, English, and mixed-language handwriting\n- **Mixed content**: Can recognize documents with both handwritten and printed text\n- **Local file & URL**: Supports both local files and remote URLs\n\n## Resource Links \u002F 资源链接\n\n| Resource        | Link                                                                           |\n| --------------- | ------------------------------------------------------------------------------ |\n| **Get API Key** | [智谱开放平台 API Keys](https:\u002F\u002Fbigmodel.cn\u002Fusercenter\u002Fproj-mgmt\u002Fapikeys)      |\n| **API Docs**    | [Layout Parsing \u002F 版面解析](https:\u002F\u002Fdocs.bigmodel.cn\u002Fapi-reference\u002F%E6%A8%A1%E5%9E%8B-api\u002F%E6%96%87%E6%A1%A3%E8%A7%A3%E6%9E%90) |\n\n## Prerequisites \u002F 前置条件\n\n### API Key Setup \u002F API Key 配置（Required \u002F 必需）\n\n脚本通过 `ZHIPU_API_KEY` 环境变量获取密钥，可与其他智谱技能复用同一个 key。\nThis script reads the key from the `ZHIPU_API_KEY` environment variable. Reusing the same key across Zhipu skills is optional.\n\n**Get Key \u002F 获取 Key：** Visit [智谱开放平台 API Keys](https:\u002F\u002Fbigmodel.cn\u002Fusercenter\u002Fproj-mgmt\u002Fapikeys) to create or copy your key.\n\n**Setup options \u002F 配置方式（任选一种）：**\n\n1. **Global config (recommended) \u002F 全局配置（推荐）：** Set once in `openclaw.json` under `env.vars`, all Zhipu skills will share it:\n\n   ```json\n   {\n     \"env\": {\n       \"vars\": {\n         \"ZHIPU_API_KEY\": \"你的密钥\"\n       }\n     }\n   }\n   ```\n\n2. **Skill-level config \u002F Skill 级别配置：** Set for this skill only in `openclaw.json`:\n\n   ```json\n   {\n     \"skills\": {\n       \"entries\": {\n         \"glmocr-handwriting\": {\n           \"env\": {\n             \"ZHIPU_API_KEY\": \"你的密钥\"\n           }\n         }\n       }\n     }\n   }\n   ```\n\n3. **Shell environment variable \u002F Shell 环境变量：** Add to `~\u002F.zshrc`:\n   ```bash\n   export ZHIPU_API_KEY=\"你的密钥\"\n   ```\n\n> 💡 如果你已为其他智谱 skill（如 `glmocr`、`glmv-caption`、`glm-image-generation`）配置过 key，它们共享同一个 `ZHIPU_API_KEY`，无需重复配置。\n\n## Security & Transparency \u002F 安全与透明度\n\n- **Environment variables used \u002F 使用的环境变量：**\n  - `ZHIPU_API_KEY` (required \u002F 必需)\n  - `GLM_OCR_TIMEOUT` (optional timeout seconds \u002F 可选超时秒数)\n- **Fixed endpoint \u002F 固定官方端点：** `https:\u002F\u002Fopen.bigmodel.cn\u002Fapi\u002Fpaas\u002Fv4\u002Flayout_parsing`\n- **No custom API URL override \u002F 不支持自定义 API URL 覆盖：** avoids accidental key exfiltration via redirected endpoints.\n- **Raw upstream response is optional \u002F 原始响应默认不返回：** use `--include-raw` only when needed for debugging.\n\n**⛔ MANDATORY RESTRICTIONS \u002F 强制限制 ⛔**\n\n1. **ONLY use GLM-OCR API** — Execute the script `python scripts\u002Fglm_ocr_cli.py`\n2. **NEVER parse handwriting yourself** — Do NOT try to read handwritten text using built-in vision or any other method\n3. **NEVER offer alternatives** — Do NOT suggest \"I can try to read it\" or similar\n4. **IF API fails** — Display the error message and STOP immediately\n5. **NO fallback methods** — Do NOT attempt handwriting recognition any other way\n\n### 📋 Output Display Rules \u002F 输出展示规则\n\nAfter running the script, present the OCR result clearly and safely.\n\n- Show extracted handwritten text (`text`) in full\n- Summarization is allowed, but do not hide important extraction failures\n- If the result file is saved, tell the user the file path\n- Show raw upstream response only when explicitly requested or debugging (`--include-raw`)\n\n## How to Use \u002F 使用方法\n\n### Recognize from URL \u002F 从 URL 识别\n\n```bash\npython scripts\u002Fglm_ocr_cli.py --file-url \"https:\u002F\u002Fexample.com\u002Fhandwriting.jpg\"\n```\n\n### Recognize from Local File \u002F 从本地文件识别\n\n```bash\npython scripts\u002Fglm_ocr_cli.py --file \u002Fpath\u002Fto\u002Fnotes.png\n```\n\n### Save Result to File \u002F 保存结果到文件\n\n```bash\npython scripts\u002Fglm_ocr_cli.py --file notes.png --output result.json --pretty\n```\n\n### Include Raw Upstream Response (Debug Only) \u002F 包含原始上游响应（仅调试）\n\n```bash\npython scripts\u002Fglm_ocr_cli.py --file notes.png --output result.json --include-raw\n```\n\n## CLI Reference \u002F CLI 参数\n\n```\npython {baseDir}\u002Fscripts\u002Fglm_ocr_cli.py (--file-url URL | --file PATH) [--output FILE] [--pretty] [--include-raw]\n```\n\n| Parameter        | Required | Description                                                      |\n| ---------------- | -------- | ---------------------------------------------------------------- |\n| `--file-url`     | One of   | URL to image\u002FPDF                                                 |\n| `--file`         | One of   | Local file path to image\u002FPDF                                     |\n| `--output`, `-o` | No       | Save result JSON to file                                         |\n| `--pretty`       | No       | Pretty-print JSON output                                         |\n| `--include-raw`  | No       | Include raw upstream API response in `result` field (debug only) |\n\n## Response Format \u002F 响应格式\n\n```json\n{\n  \"ok\": true,\n  \"text\": \"Recognized handwritten text in Markdown...\",\n  \"layout_details\": [...],\n  \"result\": null,\n  \"error\": null,\n  \"source\": \"\u002Fpath\u002Fto\u002Ffile\",\n  \"source_type\": \"file\",\n  \"raw_result_included\": false\n}\n```\n\nKey fields:\n\n- `ok` — whether recognition succeeded\n- `text` — extracted text in Markdown (use this for display)\n- `layout_details` — layout analysis details\n- `error` — error details on failure\n\n## Error Handling \u002F 错误处理\n\n**API key not configured:**\n\n```\nZHIPU_API_KEY not configured. Get your API key at: https:\u002F\u002Fbigmodel.cn\u002Fusercenter\u002Fproj-mgmt\u002Fapikeys\n```\n\n→ Show exact error to user, guide them to configure\n\n**Authentication failed (401\u002F403):** API key invalid\u002Fexpired → reconfigure\n\n**Rate limit (429):** Quota exhausted → inform user to wait\n\n**File not found:** Local file missing → check path\n",{"name":5,"metadata":24,"description":7},{"openclaw":25},{"emoji":26,"homepage":27,"requires":28,"primaryEnv":30},"✍️","https:\u002F\u002Fgithub.com\u002Fzai-org\u002FGLM-OCR\u002Ftree\u002Fmain\u002Fskills\u002Fglmocr-handwriting",{"env":29,"bins":32},[30,31],"ZHIPU_API_KEY","GLM_OCR_TIMEOUT",[33],"python","main","87afe6ce96220accf50a345dea46784c8c9f210e","YYC3-Skills-技能包\u002FYYC3-Skills-技能包-skills-v4\u002Fglmocr-handwriting",0,"https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base","https:\u002F\u002Fkb.yyc3.top\u002F","https:\u002F\u002Fgithub.com\u002FYYC-Cube","万象归元于云枢 | 深栈智启新纪元","2026-11-10 10:37:32",{"source":8,"skillName":5,"commands":44,"prompt":54,"zipAvailable":55},[45,48,51],{"tool":46,"command":47},"npx","npx skills add YYC-Cube\u002FYYC3-Knowledge-Base --skill glmocr-handwriting",{"tool":49,"command":50},"bunx","bunx skills add YYC-Cube\u002FYYC3-Knowledge-Base --skill glmocr-handwriting",{"tool":52,"command":53},"pnpm","pnpm dlx skills add YYC-Cube\u002FYYC3-Knowledge-Base --skill glmocr-handwriting","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-Skills-技能包\u002FYYC3-Skills-技能包-skills-v4\u002Fglmocr-handwriting\u002FSKILL.md",true,[57],{"path":58,"resourceType":59,"resourceTypeDesc":60,"sizeBytes":61,"sourceHtmlUrl":62},"scripts\u002Fglm_ocr_cli.py","SCRIPT","脚本",12355,"https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-Skills-技能包\u002FYYC3-Skills-技能包-skills-v4\u002Fglmocr-handwriting\u002Fscripts\u002Fglm_ocr_cli.py",[64,71,78,85,92,99],{"skillNo":65,"name":66,"nameZh":6,"description":67,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":68,"categories":69,"keywords":70,"publishedAt":19},"01M7CTDWHERCXPQCP0K03A86AS","vercel-sandbox","Run agent-browser + Chrome inside Vercel Sandbox microVMs for browser automation from any Vercel-deployed app. Use when the user needs browser automation in a Vercel app (Next.js, SvelteKit, Nuxt, Remix, Astro, etc.), wants to run headless Chrome without binary size limits, needs persistent browser sessions across commands, or wants ephemeral isolated browser environments. Triggers include \"Vercel Sandbox browser\", \"microVM Chrome\", \"agent-browser in sandbox\", \"browser automation on Vercel\", or any task requiring Chrome in a Vercel Sandbox.","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-WebSpec-Web标准\u002FYYC3-WebSpec-Web标准-standards\u002Fbrowser-agent\u002Fskills\u002Fvercel-sandbox\u002FSKILL.md",[],[],{"skillNo":72,"name":73,"nameZh":6,"description":74,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":75,"categories":76,"keywords":77,"publishedAt":19},"01M7CTD8D2BNJY54S65M47HEJA","slack","Interact with Slack workspaces using browser automation. Use when the user needs to check unread channels, navigate Slack, send messages, extract data, find information, search conversations, or automate any Slack task. Triggers include \"check my Slack\", \"what channels have unreads\", \"send a message to\", \"search Slack for\", \"extract from Slack\", \"find who said\", or any task requiring programmatic Slack interaction.","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-WebSpec-Web标准\u002FYYC3-WebSpec-Web标准-standards\u002Fbrowser-agent\u002Fskills\u002Fslack\u002FSKILL.md",[],[],{"skillNo":79,"name":80,"nameZh":6,"description":81,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":82,"categories":83,"keywords":84,"publishedAt":19},"01M7CTCSSB8ZP3Q58C3YZDZK1W","electron","Automate Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify, etc.) using agent-browser via Chrome DevTools Protocol. Use when the user needs to interact with an Electron app, automate a desktop app, connect to a running app, control a native app, or test an Electron application. Triggers include \"automate Slack app\", \"control VS Code\", \"interact with Discord app\", \"test this Electron app\", \"connect to desktop app\", or any task requiring automation of a native Electron application.","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-WebSpec-Web标准\u002FYYC3-WebSpec-Web标准-standards\u002Fbrowser-agent\u002Fskills\u002Felectron\u002FSKILL.md",[],[],{"skillNo":86,"name":87,"nameZh":6,"description":88,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":89,"categories":90,"keywords":91,"publishedAt":19},"01M7CTCBJY76688V4DCZGWFHGQ","dogfood","Systematically explore and test a web application to find bugs, UX issues, and other problems. Use when asked to \"dogfood\", \"QA\", \"exploratory test\", \"find issues\", \"bug hunt\", \"test this app\u002Fsite\u002Fplatform\", or review the quality of a web application. Produces a structured report with full reproduction evidence -- step-by-step screenshots, repro videos, and detailed repro steps for every issue -- so findings can be handed directly to the responsible teams.","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-WebSpec-Web标准\u002FYYC3-WebSpec-Web标准-standards\u002Fbrowser-agent\u002Fskills\u002Fdogfood\u002FSKILL.md",[],[],{"skillNo":93,"name":94,"nameZh":6,"description":95,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":96,"categories":97,"keywords":98,"publishedAt":19},"01M7CTC4H0FFGVEAQR9PA4GA1A","agent-browser","Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to \"open a website\", \"fill out a form\", \"click a button\", \"take a screenshot\", \"scrape data from a page\", \"test this web app\", \"login to a site\", \"automate browser actions\", or any task requiring programmatic web interaction.","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-WebSpec-Web标准\u002FYYC3-WebSpec-Web标准-standards\u002Fbrowser-agent\u002Fskills\u002Fagent-browser\u002FSKILL.md",[],[],{"skillNo":100,"name":101,"nameZh":6,"description":102,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":103,"categories":104,"keywords":105,"publishedAt":19},"01M7CTBKVFYBG78FDSABSDJTTQ","shadcn","Manages shadcn components and projects — adding, searching, fixing, debugging, styling, and composing UI, including chat interfaces. Provides project context, component docs, and usage examples. Applies when working with shadcn\u002Fui, component registries, presets, --preset codes, or any project with a components.json file. Also triggers for \"shadcn init\", \"create an app with --preset\", \"switch to --preset\", and for building a design system or applying a DESIGN.md or brand spec to shadcn\u002Fui.","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-UI-界面组件\u002FYYC3-UI-界面组件-ui\u002Fskills\u002Fshadcn\u002FSKILL.md",[],[]]