[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71HCDJ9N1FNB0V7J062P005":3,"skill-same:01M71HCDJ9N1FNB0V7J062P005":85},{"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":26,"publishedAt":47,"linkOnly":48,"markdownContent":49,"markdownBody":50,"frontMatter":51,"refName":56,"commitSha":57,"skillDirectory":58,"forksCount":59,"repositoryHtmlUrl":60,"repositoryHomepageUrl":6,"ownerHtmlUrl":61,"ownerBlogUrl":62,"ownerDescription":63,"updatedAt":64,"install":65,"resources":78},"01M71HCDJ9N1FNB0V7J062P005","bgpt-paper-search",null,"Search scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server. Returns 25+ fields per paper including methods, results, sample sizes, quality scores, and conclusions. Use for literature reviews, evidence synthesis, and finding experimental details not available in abstracts alone.","iDorgham\u002FWorkspace-Factory","iDorgham","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F136521493?v=4","01M6CNGBDAHE4ARW3YJEF4X2FD","Dorgham","01M71E8H3CXZ7DJX59MTM9JEB2",1,"MIT","https:\u002F\u002Fgithub.com\u002FiDorgham\u002FWorkspace-Factory\u002Fblob\u002Fmaster\u002Ffactory\u002Flibrary\u002Fskills\u002Fgithub_imports\u002Fbgpt-paper-search\u002FSKILL.md",[18,23],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000021","资料检索与研究","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",[27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46],"paper search","search","paper","bgpt paper search","methods","for","papers","reviews","scientific","literature","sample","MCP","evidence synthesis","evidence","use","text","Bash","server","mcp server","github","2026-11-10 10:12:30",false,"---\nname: bgpt-paper-search\ndescription: Search scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server. Returns 25+ fields per paper including methods, results, sample sizes, quality scores, and conclusions. Use for literature reviews, evidence synthesis, and finding experimental details not available in abstracts alone.\nallowed-tools: Bash\nlicense: MIT\nmetadata:\n    skill-author: BGPT\n    website: https:\u002F\u002Fbgpt.pro\u002Fmcp\n    github: https:\u002F\u002Fgithub.com\u002Fconnerlambden\u002Fbgpt-mcp\n---\n\n# BGPT Paper Search\n\n## Overview\n\nBGPT is a remote MCP server that searches a curated database of scientific papers built from raw experimental data extracted from full-text studies. Unlike traditional literature databases that return titles and abstracts, BGPT returns structured data from the actual paper content — methods, quantitative results, sample sizes, quality assessments, and 25+ metadata fields per paper.\n\n## When to Use This Skill\n\nUse this skill when:\n- Searching for scientific papers with specific experimental details\n- Conducting systematic or scoping literature reviews\n- Finding quantitative results, sample sizes, or effect sizes across studies\n- Comparing methodologies used in different studies\n- Looking for papers with quality scores or evidence grading\n- Needing structured data from full-text papers (not just abstracts)\n- Building evidence tables for meta-analyses or clinical guidelines\n\n## Setup\n\nBGPT is a remote MCP server — no local installation required.\n\n### Claude Desktop \u002F Claude Code\n\nAdd to your MCP configuration:\n\n```json\n{\n  \"mcpServers\": {\n    \"bgpt\": {\n      \"command\": \"npx\",\n      \"args\": [\"mcp-remote\", \"https:\u002F\u002Fbgpt.pro\u002Fmcp\u002Fsse\"]\n    }\n  }\n}\n```\n\n### npm (alternative)\n\n```bash\nnpx bgpt-mcp\n```\n\n## Usage\n\nOnce configured, use the `search_papers` tool provided by the BGPT MCP server:\n\n```\nSearch for papers about: \"CRISPR gene editing efficiency in human cells\"\n```\n\nThe server returns structured results including:\n- **Title, authors, journal, year, DOI**\n- **Methods**: Experimental techniques, models, protocols\n- **Results**: Key findings with quantitative data\n- **Sample sizes**: Number of subjects\u002Fsamples\n- **Quality scores**: Study quality assessments\n- **Conclusions**: Author conclusions and implications\n\n## Pricing\n\n- **Free tier**: 50 searches per network, no API key required\n- **Paid**: $0.01 per result with an API key from [bgpt.pro\u002Fmcp](https:\u002F\u002Fbgpt.pro\u002Fmcp)\n\n","# BGPT Paper Search\n\n## Overview\n\nBGPT is a remote MCP server that searches a curated database of scientific papers built from raw experimental data extracted from full-text studies. Unlike traditional literature databases that return titles and abstracts, BGPT returns structured data from the actual paper content — methods, quantitative results, sample sizes, quality assessments, and 25+ metadata fields per paper.\n\n## When to Use This Skill\n\nUse this skill when:\n- Searching for scientific papers with specific experimental details\n- Conducting systematic or scoping literature reviews\n- Finding quantitative results, sample sizes, or effect sizes across studies\n- Comparing methodologies used in different studies\n- Looking for papers with quality scores or evidence grading\n- Needing structured data from full-text papers (not just abstracts)\n- Building evidence tables for meta-analyses or clinical guidelines\n\n## Setup\n\nBGPT is a remote MCP server — no local installation required.\n\n### Claude Desktop \u002F Claude Code\n\nAdd to your MCP configuration:\n\n```json\n{\n  \"mcpServers\": {\n    \"bgpt\": {\n      \"command\": \"npx\",\n      \"args\": [\"mcp-remote\", \"https:\u002F\u002Fbgpt.pro\u002Fmcp\u002Fsse\"]\n    }\n  }\n}\n```\n\n### npm (alternative)\n\n```bash\nnpx bgpt-mcp\n```\n\n## Usage\n\nOnce configured, use the `search_papers` tool provided by the BGPT MCP server:\n\n```\nSearch for papers about: \"CRISPR gene editing efficiency in human cells\"\n```\n\nThe server returns structured results including:\n- **Title, authors, journal, year, DOI**\n- **Methods**: Experimental techniques, models, protocols\n- **Results**: Key findings with quantitative data\n- **Sample sizes**: Number of subjects\u002Fsamples\n- **Quality scores**: Study quality assessments\n- **Conclusions**: Author conclusions and implications\n\n## Pricing\n\n- **Free tier**: 50 searches per network, no API key required\n- **Paid**: $0.01 per result with an API key from [bgpt.pro\u002Fmcp](https:\u002F\u002Fbgpt.pro\u002Fmcp)\n\n",{"name":5,"license":15,"metadata":52,"description":7,"allowed-tools":43},{"github":53,"website":54,"skill-author":55},"https:\u002F\u002Fgithub.com\u002Fconnerlambden\u002Fbgpt-mcp","https:\u002F\u002Fbgpt.pro\u002Fmcp","BGPT","master","c2e410e11df4d80d885e0ecf0583ef3c926df736","factory\u002Flibrary\u002Fskills\u002Fgithub_imports\u002Fbgpt-paper-search",0,"https:\u002F\u002Fgithub.com\u002FiDorgham\u002FWorkspace-Factory","https:\u002F\u002Fgithub.com\u002FiDorgham","Dorgham.me","hey I'm Dorgham \r\nI code, I create, and AI codes back. \r\nMaybe we can give AI the chance!! now we begin. 🚀🤖\r\n... . . . git commit -m \"Hello, Future\" ","2026-05-04 18:39:09",{"source":8,"skillName":5,"commands":66,"prompt":76,"zipAvailable":77},[67,70,73],{"tool":68,"command":69},"npx","npx skills add iDorgham\u002FWorkspace-Factory --skill bgpt-paper-search",{"tool":71,"command":72},"bunx","bunx skills add iDorgham\u002FWorkspace-Factory --skill bgpt-paper-search",{"tool":74,"command":75},"pnpm","pnpm dlx skills add iDorgham\u002FWorkspace-Factory --skill bgpt-paper-search","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FiDorgham\u002FWorkspace-Factory\u002Fblob\u002Fmaster\u002Ffactory\u002Flibrary\u002Fskills\u002Fgithub_imports\u002Fbgpt-paper-search\u002FSKILL.md",true,[79],{"path":80,"resourceType":81,"resourceTypeDesc":82,"sizeBytes":83,"sourceHtmlUrl":84},"_AIWF_IMPORT.json","REFERENCE","参考文档",371,"https:\u002F\u002Fgithub.com\u002FiDorgham\u002FWorkspace-Factory\u002Fblob\u002Fmaster\u002Ffactory\u002Flibrary\u002Fskills\u002Fgithub_imports\u002Fbgpt-paper-search\u002F_AIWF_IMPORT.json",[86,117,139,161,180,203],{"skillNo":87,"name":88,"nameZh":6,"description":89,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":90,"categories":91,"keywords":95,"publishedAt":116},"01M71P8WVBMB2X3D24R0YT0B0E","vercel-react-view-transitions","Guide for implementing smooth, native-feeling animations using React's View Transition API (`\u003CViewTransition>` component, `addTransitionType`, and CSS view transition pseudo-elements). Use this skill whenever the user wants to add page transitions, animate route changes, create shared element animations, animate enter\u002Fexit of components, animate list reorder, implement directional (forward\u002Fback) navigation animations, or integrate view transitions in Next.js. Also use when the user mentions view transitions, `startViewTransition`, `ViewTransition`, transition types, or asks about animating between UI states in React without third-party animation libraries.","https:\u002F\u002Fgithub.com\u002FiDorgham\u002FWorkspace-Factory\u002Fblob\u002Fmaster\u002Ffactory\u002Flibrary\u002Fskills\u002Fofficial_vercel_labs_react_view_transitions\u002Fskill.md",[92],{"categoryNo":93,"categoryName":94,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000009","前端开发",[96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115],"react","vercel react view transitions","view","react view transitions","vercel","transitions","shared","back","Animation","css","types","states","element","implementing","when","components","api","route","create","libraries","2026-11-10 13:02:02",{"skillNo":118,"name":119,"nameZh":6,"description":120,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":121,"categories":122,"keywords":124,"publishedAt":116},"01M71P8TDGHZ289TSAC5VTG2EW","vercel-react-native-skills","React Native and Expo best practices for building performant mobile apps. Use when building React Native components, optimizing list performance, implementing animations, or working with native modules. Triggers on tasks involving React Native, Expo, mobile performance, or native platform APIs.","https:\u002F\u002Fgithub.com\u002FiDorgham\u002FWorkspace-Factory\u002Fblob\u002Fmaster\u002Ffactory\u002Flibrary\u002Fskills\u002Fofficial_vercel_labs_react_native_skills\u002Fskill.md",[123],{"categoryNo":93,"categoryName":94,"taxonomyType":21,"taxonomyTypeDesc":22},[96,125,126,100,127,128,129,130,109,131,110,132,111,133,134,135,136,137,138,32],"react native","native","vercel react native skills","react native skills","modules","performance","apps","tasks","mobile","expo","list","mobile performance","platform","animations",{"skillNo":140,"name":141,"nameZh":6,"description":142,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":143,"categories":144,"keywords":146,"publishedAt":116},"01M71P8QK4JF5BYRGYDDGPZQG9","vercel-react-best-practices","React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React\u002FNext.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.","https:\u002F\u002Fgithub.com\u002FiDorgham\u002FWorkspace-Factory\u002Fblob\u002Fmaster\u002Ffactory\u002Flibrary\u002Fskills\u002Fofficial_vercel_labs_react_best_practices\u002Fskill.md",[145],{"categoryNo":93,"categoryName":94,"taxonomyType":21,"taxonomyTypeDesc":22},[96,147,148,100,149,130,150,110,151,132,111,152,153,154,155,156,157,158,159,160],"react best practices","vercel react best practices","best practices","writing","code","data fetching","react components","next","refactoring","data","patterns","Optimization","guidelines","triggers",{"skillNo":162,"name":163,"nameZh":6,"description":164,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":165,"categories":166,"keywords":168,"publishedAt":116},"01M71P8HVEA70K5N6ZVJCG2ED3","vercel-composition-patterns","React composition patterns that scale. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or designing reusable APIs. Triggers on tasks involving compound components, render props, context providers, or component architecture. Includes React 19 API changes.","https:\u002F\u002Fgithub.com\u002FiDorgham\u002FWorkspace-Factory\u002Fblob\u002Fmaster\u002Ffactory\u002Flibrary\u002Fskills\u002Fofficial_vercel_labs_composition_patterns\u002Fskill.md",[167],{"categoryNo":93,"categoryName":94,"taxonomyType":21,"taxonomyTypeDesc":22},[169,100,170,157,171,172,173,174,160,175,176,41,110,177,132,111,178,179,112,96],"Composition","composition patterns","vercel composition patterns","react composition patterns","react 19","render","boolean","component architecture","reusable","architecture","react composition",{"skillNo":181,"name":182,"nameZh":6,"description":183,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":184,"categories":185,"keywords":189,"publishedAt":116},"01M71P60XXKKP222ZFJRG7R373","supabase-postgres-best-practices","Postgres performance optimization and best practices from Supabase. Use this skill when writing, reviewing, or optimizing Postgres queries, schema designs, or database configurations.","https:\u002F\u002Fgithub.com\u002FiDorgham\u002FWorkspace-Factory\u002Fblob\u002Fmaster\u002Ffactory\u002Flibrary\u002Fskills\u002Fofficial_supabase_supabase_postgres_best_practices\u002Fskill.md",[186],{"categoryNo":187,"categoryName":188,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000010","后端与接口",[190,191,192,193,149,194,195,196,32,158,130,197,198,150,199,41,200,201,202,110],"postgres best practices","supabase","postgres","supabase postgres best practices","categories","postgres performance","advanced","correct","schema","impact","Rules","critical","database",{"skillNo":204,"name":205,"nameZh":6,"description":206,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":207,"categories":208,"keywords":210,"publishedAt":224},"01M71P2ZCEJD0PKC458YTP1FJW","portable-text-serialization","Render and serialize Portable Text to React, Svelte, Vue, Astro, HTML, Markdown, and plain text. Use when implementing Portable Text rendering in any frontend framework, building custom serializers for non-standard block types, converting Portable Text to HTML strings server-side, converting Portable Text to Markdown, extracting plain text from Portable Text, or troubleshooting rendering issues with marks, blocks, lists, or custom types.","https:\u002F\u002Fgithub.com\u002FiDorgham\u002FWorkspace-Factory\u002Fblob\u002Fmaster\u002Ffactory\u002Flibrary\u002Fskills\u002Fofficial_sanity_io_portable_text_serialization\u002Fskill.md",[209],{"categoryNo":93,"categoryName":94,"taxonomyType":21,"taxonomyTypeDesc":22},[42,211,212,213,214,106,215,174,216,109,217,218,110,96,219,220,44,221,222,223],"portable text serialization","portable","serialization","extracting","strings","issues","frontend","svelte","sanity","astro","markdown","rendering","vue","2026-11-10 10:56:23"]