[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71HHNX3X7XZHT33YN2NTPWJ":3,"skill-same:01M71HHNX3X7XZHT33YN2NTPWJ":100},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":25,"publishedAt":46,"linkOnly":47,"markdownContent":48,"markdownBody":49,"frontMatter":50,"refName":58,"commitSha":59,"skillDirectory":60,"forksCount":61,"repositoryHtmlUrl":62,"repositoryHomepageUrl":6,"ownerHtmlUrl":63,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":64,"install":65,"resources":77},"01M71HHNX3X7XZHT33YN2NTPWJ","tavily-web",null,"Web research skill using Tavily API for search, extract, crawl, map, and structured research tasks. Use when you need latest information, extract content from URLs, or discover site structure. Triggers: tavily, web search, search web, latest info, extract, crawl, map, research, 搜索网页, 查资料, 最新","JSGforever\u002Fskillguard","JSGforever","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F85541948?v=4","01M71FQD3E132VMR5F4TAYX3YS","01M71FQD4DYW0XJ4XQ4YQH75Y9",2,"GPL-3.0","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__benedictking--tavily-web\u002FSKILL.md",[17,22],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",{"categoryNo":23,"categoryName":24,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000021","资料检索与研究",[26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45],"web","tavily web","tavily","info","task","api","tasks","Bash","you","when","information","use","map","true","triggers","search","web search","for","crawl","discover","2026-11-10 10:12:30",false,"---\nname: tavily-web\nversion: 1.0.3\nauthor: BenedictKing\ndescription: \"Web research skill using Tavily API for search, extract, crawl, map, and structured research tasks. Use when you need latest information, extract content from URLs, or discover site structure. Triggers: tavily, web search, search web, latest info, extract, crawl, map, research, 搜索网页, 查资料, 最新\"\nallowed-tools:\n  - Task\n  - Bash\n  - Read\n  - Write\nuser-invocable: true\n---\n\n# Tavily Web Skill\n\n## Trigger Conditions & Endpoint Selection\n\nChoose Tavily endpoint based on user intent:\n\n- **search**: Need to \"search web \u002F latest info \u002F find sources \u002F find links\"\n- **extract**: Given URL(s), need to extract\u002Fsummarize content\n- **crawl**: Need to traverse site following instructions and scrape page content\n- **map**: Need to discover site page list\u002Fstructure (without full content or metadata only)\n- **research**: Need structured research output following given `output_schema`\n\n## Recommended Architecture (Main Skill + Sub-skill)\n\nThis skill uses a two-phase architecture:\n\n1. **Main skill (current context)**: Understand user question → Choose endpoint → Assemble JSON payload\n2. **Sub-skill (fork context)**: Only responsible for HTTP call execution, avoiding conversation history token waste\n\n## Execution Method\n\nUse Task tool to invoke `tavily-fetcher` sub-skill, passing command and JSON (stdin):\n\n```\nTask parameters:\n- subagent_type: Bash\n- description: \"Call Tavily API\"\n- prompt: cat \u003C\u003C'JSON' | node .claude\u002Fskills\u002Ftavily-web\u002Ftavily-api.cjs \u003Csearch|extract|crawl|map|research>\n  { ...payload... }\n  JSON\n```\n\n## Payload Examples (Based on Provided curl)\n\n### 1) Search the web\n\n```bash\ncat \u003C\u003C'JSON' | node .claude\u002Fskills\u002Ftavily-web\u002Ftavily-api.cjs search\n{\n  \"query\": \"who is Leo Messi?\",\n  \"auto_parameters\": false,\n  \"topic\": \"general\",\n  \"search_depth\": \"basic\",\n  \"chunks_per_source\": 3,\n  \"max_results\": 1,\n  \"time_range\": null,\n  \"start_date\": \"2025-02-09\",\n  \"end_date\": \"2025-12-29\",\n  \"include_answer\": false,\n  \"include_raw_content\": false,\n  \"include_images\": false,\n  \"include_image_descriptions\": false,\n  \"include_favicon\": false,\n  \"include_domains\": [],\n  \"exclude_domains\": [],\n  \"country\": null,\n  \"include_usage\": false\n}\nJSON\n```\n\n### 2) Extract webpages\n\n```bash\ncat \u003C\u003C'JSON' | node .claude\u002Fskills\u002Ftavily-web\u002Ftavily-api.cjs extract\n{\n  \"urls\": \"https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FArtificial_intelligence\",\n  \"query\": \"\u003Cstring>\",\n  \"chunks_per_source\": 3,\n  \"extract_depth\": \"basic\",\n  \"include_images\": false,\n  \"include_favicon\": false,\n  \"format\": \"markdown\",\n  \"timeout\": \"None\",\n  \"include_usage\": false\n}\nJSON\n```\n\n### 3) Crawl webpages\n\n```bash\ncat \u003C\u003C'JSON' | node .claude\u002Fskills\u002Ftavily-web\u002Ftavily-api.cjs crawl\n{\n  \"url\": \"docs.tavily.com\",\n  \"instructions\": \"Find all pages about the Python SDK\",\n  \"chunks_per_source\": 3,\n  \"max_depth\": 1,\n  \"max_breadth\": 20,\n  \"limit\": 50,\n  \"select_paths\": null,\n  \"select_domains\": null,\n  \"exclude_paths\": null,\n  \"exclude_domains\": null,\n  \"allow_external\": true,\n  \"include_images\": false,\n  \"extract_depth\": \"basic\",\n  \"format\": \"markdown\",\n  \"include_favicon\": false,\n  \"timeout\": 150,\n  \"include_usage\": false\n}\nJSON\n```\n\n### 4) Map webpages\n\n```bash\ncat \u003C\u003C'JSON' | node .claude\u002Fskills\u002Ftavily-web\u002Ftavily-api.cjs map\n{\n  \"url\": \"docs.tavily.com\",\n  \"instructions\": \"Find all pages about the Python SDK\",\n  \"max_depth\": 1,\n  \"max_breadth\": 20,\n  \"limit\": 50,\n  \"select_paths\": null,\n  \"select_domains\": null,\n  \"exclude_paths\": null,\n  \"exclude_domains\": null,\n  \"allow_external\": true,\n  \"timeout\": 150,\n  \"include_usage\": false\n}\nJSON\n```\n\n### 5) Create Research Task\n\n```bash\ncat \u003C\u003C'JSON' | node .claude\u002Fskills\u002Ftavily-web\u002Ftavily-api.cjs research\n{\n  \"input\": \"What are the latest developments in AI?\",\n  \"model\": \"auto\",\n  \"stream\": false,\n  \"output_schema\": {\n    \"properties\": {\n      \"company\": {\n        \"type\": \"string\",\n        \"description\": \"The name of the company\"\n      },\n      \"key_metrics\": {\n        \"type\": \"array\",\n        \"description\": \"List of key performance metrics\",\n        \"items\": {\n          \"type\": \"string\"\n        }\n      },\n      \"financial_details\": {\n        \"type\": \"object\",\n        \"description\": \"Detailed financial breakdown\",\n        \"properties\": {\n          \"operating_income\": {\n            \"type\": \"number\",\n            \"description\": \"Operating income for the period\"\n          }\n        }\n      }\n    },\n    \"required\": [\n      \"company\"\n    ]\n  },\n  \"citation_format\": \"numbered\"\n}\nJSON\n```\n\n## Environment Variables & API Key\n\nTwo ways to configure API Key (priority: environment variable > `.env`):\n\n1. Environment variable: `TAVILY_API_KEY`\n2. `.env` file: Place in `.claude\u002Fskills\u002Ftavily-web\u002F.env`, can copy from `.env.example`\n","# Tavily Web Skill\n\n## Trigger Conditions & Endpoint Selection\n\nChoose Tavily endpoint based on user intent:\n\n- **search**: Need to \"search web \u002F latest info \u002F find sources \u002F find links\"\n- **extract**: Given URL(s), need to extract\u002Fsummarize content\n- **crawl**: Need to traverse site following instructions and scrape page content\n- **map**: Need to discover site page list\u002Fstructure (without full content or metadata only)\n- **research**: Need structured research output following given `output_schema`\n\n## Recommended Architecture (Main Skill + Sub-skill)\n\nThis skill uses a two-phase architecture:\n\n1. **Main skill (current context)**: Understand user question → Choose endpoint → Assemble JSON payload\n2. **Sub-skill (fork context)**: Only responsible for HTTP call execution, avoiding conversation history token waste\n\n## Execution Method\n\nUse Task tool to invoke `tavily-fetcher` sub-skill, passing command and JSON (stdin):\n\n```\nTask parameters:\n- subagent_type: Bash\n- description: \"Call Tavily API\"\n- prompt: cat \u003C\u003C'JSON' | node .claude\u002Fskills\u002Ftavily-web\u002Ftavily-api.cjs \u003Csearch|extract|crawl|map|research>\n  { ...payload... }\n  JSON\n```\n\n## Payload Examples (Based on Provided curl)\n\n### 1) Search the web\n\n```bash\ncat \u003C\u003C'JSON' | node .claude\u002Fskills\u002Ftavily-web\u002Ftavily-api.cjs search\n{\n  \"query\": \"who is Leo Messi?\",\n  \"auto_parameters\": false,\n  \"topic\": \"general\",\n  \"search_depth\": \"basic\",\n  \"chunks_per_source\": 3,\n  \"max_results\": 1,\n  \"time_range\": null,\n  \"start_date\": \"2025-02-09\",\n  \"end_date\": \"2025-12-29\",\n  \"include_answer\": false,\n  \"include_raw_content\": false,\n  \"include_images\": false,\n  \"include_image_descriptions\": false,\n  \"include_favicon\": false,\n  \"include_domains\": [],\n  \"exclude_domains\": [],\n  \"country\": null,\n  \"include_usage\": false\n}\nJSON\n```\n\n### 2) Extract webpages\n\n```bash\ncat \u003C\u003C'JSON' | node .claude\u002Fskills\u002Ftavily-web\u002Ftavily-api.cjs extract\n{\n  \"urls\": \"https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FArtificial_intelligence\",\n  \"query\": \"\u003Cstring>\",\n  \"chunks_per_source\": 3,\n  \"extract_depth\": \"basic\",\n  \"include_images\": false,\n  \"include_favicon\": false,\n  \"format\": \"markdown\",\n  \"timeout\": \"None\",\n  \"include_usage\": false\n}\nJSON\n```\n\n### 3) Crawl webpages\n\n```bash\ncat \u003C\u003C'JSON' | node .claude\u002Fskills\u002Ftavily-web\u002Ftavily-api.cjs crawl\n{\n  \"url\": \"docs.tavily.com\",\n  \"instructions\": \"Find all pages about the Python SDK\",\n  \"chunks_per_source\": 3,\n  \"max_depth\": 1,\n  \"max_breadth\": 20,\n  \"limit\": 50,\n  \"select_paths\": null,\n  \"select_domains\": null,\n  \"exclude_paths\": null,\n  \"exclude_domains\": null,\n  \"allow_external\": true,\n  \"include_images\": false,\n  \"extract_depth\": \"basic\",\n  \"format\": \"markdown\",\n  \"include_favicon\": false,\n  \"timeout\": 150,\n  \"include_usage\": false\n}\nJSON\n```\n\n### 4) Map webpages\n\n```bash\ncat \u003C\u003C'JSON' | node .claude\u002Fskills\u002Ftavily-web\u002Ftavily-api.cjs map\n{\n  \"url\": \"docs.tavily.com\",\n  \"instructions\": \"Find all pages about the Python SDK\",\n  \"max_depth\": 1,\n  \"max_breadth\": 20,\n  \"limit\": 50,\n  \"select_paths\": null,\n  \"select_domains\": null,\n  \"exclude_paths\": null,\n  \"exclude_domains\": null,\n  \"allow_external\": true,\n  \"timeout\": 150,\n  \"include_usage\": false\n}\nJSON\n```\n\n### 5) Create Research Task\n\n```bash\ncat \u003C\u003C'JSON' | node .claude\u002Fskills\u002Ftavily-web\u002Ftavily-api.cjs research\n{\n  \"input\": \"What are the latest developments in AI?\",\n  \"model\": \"auto\",\n  \"stream\": false,\n  \"output_schema\": {\n    \"properties\": {\n      \"company\": {\n        \"type\": \"string\",\n        \"description\": \"The name of the company\"\n      },\n      \"key_metrics\": {\n        \"type\": \"array\",\n        \"description\": \"List of key performance metrics\",\n        \"items\": {\n          \"type\": \"string\"\n        }\n      },\n      \"financial_details\": {\n        \"type\": \"object\",\n        \"description\": \"Detailed financial breakdown\",\n        \"properties\": {\n          \"operating_income\": {\n            \"type\": \"number\",\n            \"description\": \"Operating income for the period\"\n          }\n        }\n      }\n    },\n    \"required\": [\n      \"company\"\n    ]\n  },\n  \"citation_format\": \"numbered\"\n}\nJSON\n```\n\n## Environment Variables & API Key\n\nTwo ways to configure API Key (priority: environment variable > `.env`):\n\n1. Environment variable: `TAVILY_API_KEY`\n2. `.env` file: Place in `.claude\u002Fskills\u002Ftavily-web\u002F.env`, can copy from `.env.example`\n",{"name":5,"author":51,"version":52,"description":7,"allowed-tools":53,"user-invocable":57},"BenedictKing","1.0.3",[54,33,55,56],"Task","Read","Write",true,"main","f2ec4b3b9133d34eeaf9b38e4b0a97e8e5705a7f","benchmarks\u002Ffinal\u002Fskills\u002Fasset1__benedictking--tavily-web",0,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard","https:\u002F\u002Fgithub.com\u002FJSGforever","2026-08-29 18:27:56",{"source":8,"skillName":5,"commands":66,"prompt":76,"zipAvailable":57},[67,70,73],{"tool":68,"command":69},"npx","npx skills add JSGforever\u002Fskillguard --skill tavily-web",{"tool":71,"command":72},"bunx","bunx skills add JSGforever\u002Fskillguard --skill tavily-web",{"tool":74,"command":75},"pnpm","pnpm dlx skills add JSGforever\u002Fskillguard --skill tavily-web","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__benedictking--tavily-web\u002FSKILL.md",[78,84,88,94],{"path":79,"resourceType":80,"resourceTypeDesc":81,"sizeBytes":82,"sourceHtmlUrl":83},".env.example","OTHER","其他",118,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__benedictking--tavily-web\u002F.env.example",{"path":85,"resourceType":80,"resourceTypeDesc":81,"sizeBytes":86,"sourceHtmlUrl":87},".gitignore",26,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__benedictking--tavily-web\u002F.gitignore",{"path":89,"resourceType":90,"resourceTypeDesc":91,"sizeBytes":92,"sourceHtmlUrl":93},"tavily-api.cjs","SCRIPT","脚本",5417,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__benedictking--tavily-web\u002Ftavily-api.cjs",{"path":95,"resourceType":96,"resourceTypeDesc":97,"sizeBytes":98,"sourceHtmlUrl":99},"tavily-fetcher.md","REFERENCE","参考文档",773,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__benedictking--tavily-web\u002Ftavily-fetcher.md",[101,130,146,172,194,215],{"skillNo":102,"name":103,"nameZh":6,"description":104,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":105,"categories":106,"keywords":110,"publishedAt":46},"01M71HY2SNXBA9Q00WZDTZQ31Z","skillguard-codex-scanner","Hybrid deterministic+LLM agent-skill security scanner. Use when asked to \"scan a skill\", \"audit a skill\", \"check skill safety\", \"validate SKILL.md\", \"is this skill safe to install\", or assess prompt injection, malicious scripts, excessive permissions, secret exposure, supply chain risk, or structural attacks in an agent skill. Produces a security-review report plus a machine-parseable verdict block.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fsrc\u002Fskillguard\u002Fstatic_scanner\u002Fskillguard-codex-scanner\u002FSKILL.md",[107],{"categoryNo":108,"categoryName":109,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发",[111,112,113,114,115,116,117,118,119,120,121,122,35,123,124,125,126,127,128,129],"scanner","skillguard codex scanner","skillguard","codex","chain","skill security","security-review","review report","structural","secret","prompt injection","security scanner","review","malicious","permissions","exposure","audit","scripts","safe",{"skillNo":131,"name":132,"nameZh":6,"description":133,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":134,"licenseFileUrl":6,"sourceHtmlUrl":135,"categories":136,"keywords":142,"publishedAt":46},"01M71HY0SPKTT3S27BC2HPAC5M","data-exfiltrator","Analyzes data files","MIT","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Fsmoke-one-skill\u002Fasset1__cisco-ai-defense--data-exfiltrator\u002FSKILL.md",[137],{"categoryNo":138,"categoryName":139,"taxonomyType":140,"taxonomyTypeDesc":141},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[143,144,145],"data","data exfiltrator","files",{"skillNo":147,"name":148,"nameZh":6,"description":149,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":150,"categories":151,"keywords":152,"publishedAt":46},"01M71HXVS9EMN44BGDW215FZ72","real-time-collaboration-engine","Build real-time collaborative editing with WebSockets, OT\u002FCRDT conflict resolution, and presence awareness. Implements cursor tracking, optimistic updates, and offline sync. Use for collaborative editors, whiteboards, video editing. Activate on \"real-time collaboration\", \"WebSocket sync\", \"multiplayer editing\", \"CRDT\", \"presence awareness\". NOT for simple chat, request-response APIs, or single-user apps.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__curiositech--real-time-collaboration-engine\u002FSKILL.md",[],[153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,33,168,169,170,171],"time","real time collaboration engine","real time collaboration","collaboration","engine","real time","Video","reliability","video editing","performance","conflict resolution","presence","access","apps","updates","activate","optimizer","react","streaming",{"skillNo":173,"name":174,"nameZh":6,"description":175,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":176,"categories":177,"keywords":181,"publishedAt":46},"01M71HXP6CTY4KFN0QVMMN0V7J","react-performance-optimizer","Optimize React apps for 60fps performance. Implements memoization, virtualization, code splitting, bundle optimization. Use for slow renders, large lists, bundle bloat. Activate on \"React performance\", \"slow render\", \"useMemo\", \"bundle size\", \"virtualization\". NOT for backend optimization, non-React frameworks, or premature optimization.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__curiositech--react-performance-optimizer\u002FSKILL.md",[178],{"categoryNo":179,"categoryName":180,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000009","前端开发",[162,182,169,170,183,184,185,186,187,188,153,189,190,166,33,191,168,171,192,193],"react performance optimizer","react performance","performance optimizer","app","nextjs","expert","re","render","2025","code","router","strategies",{"skillNo":195,"name":196,"nameZh":6,"description":197,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":198,"categories":199,"keywords":201,"publishedAt":46},"01M71HXH7QXSQB4QTDZ7SP7YXQ","llm-streaming-response-handler","Build production LLM streaming UIs with Server-Sent Events, real-time token display, cancellation, error recovery. Handles OpenAI\u002FAnthropic\u002FClaude streaming APIs. Use for chatbots, AI assistants, real-time text generation. Activate on \"LLM streaming\", \"SSE\", \"token stream\", \"chat UI\", \"real-time AI\". NOT for batch processing, non-streaming APIs, or WebSocket bidirectional chat.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__curiositech--llm-streaming-response-handler\u002FSKILL.md",[200],{"categoryNo":179,"categoryName":180,"taxonomyType":20,"taxonomyTypeDesc":21},[202,171,203,204,205,206,162,153,207,208,209,33,168,169,210,170,211,212,213,214],"llm streaming response handler","handler","error","processing","retry","chat ui","error recovery","critical","batch","display","text","server","read",{"skillNo":216,"name":217,"nameZh":6,"description":218,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":219,"categories":220,"keywords":228,"publishedAt":46},"01M71HXCB0E1YRKYW1Y8T0Y106","github-actions-pipeline-builder","Build production CI\u002FCD pipelines with GitHub Actions. Implements matrix builds, caching, deployments, testing, security scanning. Use for automated testing, deployments, release workflows. Activate on \"GitHub Actions\", \"CI\u002FCD\", \"workflow\", \"deployment pipeline\", \"automated testing\". NOT for Jenkins\u002FCircleCI, manual deployments, or non-GitHub repositories.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__curiositech--github-actions-pipeline-builder\u002FSKILL.md",[221,224,227],{"categoryNo":222,"categoryName":223,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":225,"categoryName":226,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000011","运维与部署",{"categoryNo":108,"categoryName":109,"taxonomyType":20,"taxonomyTypeDesc":21},[229,230,231,232,233,234,235,160,187,236,237,238,168,193,239,214,240,241,242,243],"github actions pipeline builder","actions","github actions","pipeline builder","github","builder","pipeline","testing","ci","workflows","run","release","write","edit","git"]