[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6FZCD72TRBZPCSYSTRSE6QA":3,"skill-same:01M6FZCD72TRBZPCSYSTRSE6QA":77},{"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":22,"publishedAt":43,"linkOnly":44,"markdownContent":45,"markdownBody":46,"frontMatter":47,"refName":50,"commitSha":51,"skillDirectory":52,"forksCount":53,"repositoryHtmlUrl":54,"repositoryHomepageUrl":6,"ownerHtmlUrl":55,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":56,"install":57,"resources":70},"01M6FZCD72TRBZPCSYSTRSE6QA","web-search",null,"Web search and content extraction with Tavily and Exa via inference.sh CLI.\nApps: Tavily Search, Tavily Extract, Exa Search, Exa Answer, Exa Extract.\nCapabilities: AI-powered search, content extraction, direct answers, research.\nUse for: research, RAG pipelines, fact-checking, content aggregation, agents.\nTriggers: web search, tavily, exa, search api, content extraction, research,\ninternet search, ai search, search assistant, web scraping, rag, perplexity alternative","kbarbel640-del\u002Fskills","kbarbel640-del","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F255315490?v=4","01M6CJPPQGCCESXMG3K7BBGQ5J","01M6CJPPX2PB2BCZERFVM2C2B3",1,"MIT","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fokaris\u002Fweb-search-2\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000021","资料检索与研究","SCENARIO","使用场景",[23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42],"web","search","web search","use","answer","internet","internet search","with","tavily search","tavily extract","apps","triggers","exa","tavily","scraping","web scraping","Bash","api","capabilities","research","2026-11-10 10:12:30",false,"---\nname: web-search\ndescription: |\n  Web search and content extraction with Tavily and Exa via inference.sh CLI.\n  Apps: Tavily Search, Tavily Extract, Exa Search, Exa Answer, Exa Extract.\n  Capabilities: AI-powered search, content extraction, direct answers, research.\n  Use for: research, RAG pipelines, fact-checking, content aggregation, agents.\n  Triggers: web search, tavily, exa, search api, content extraction, research,\n  internet search, ai search, search assistant, web scraping, rag, perplexity alternative\nallowed-tools: Bash(infsh *)\n---\n\n# Web Search & Extraction\n\nSearch the web and extract content via [inference.sh](https:\u002F\u002Finference.sh) CLI.\n\n## Quick Start\n\n```bash\ncurl -fsSL https:\u002F\u002Fcli.inference.sh | sh && infsh login\n\n# Search the web\ninfsh app run tavily\u002Fsearch-assistant --input '{\"query\": \"latest AI developments 2024\"}'\n```\n\n## Available Apps\n\n### Tavily\n\n| App | App ID | Description |\n|-----|--------|-------------|\n| Search Assistant | `tavily\u002Fsearch-assistant` | AI-powered search with answers |\n| Extract | `tavily\u002Fextract` | Extract content from URLs |\n\n### Exa\n\n| App | App ID | Description |\n|-----|--------|-------------|\n| Search | `exa\u002Fsearch` | Smart web search with AI |\n| Answer | `exa\u002Fanswer` | Direct factual answers |\n| Extract | `exa\u002Fextract` | Extract and analyze web content |\n\n## Examples\n\n### Tavily Search\n\n```bash\ninfsh app run tavily\u002Fsearch-assistant --input '{\n  \"query\": \"What are the best practices for building AI agents?\"\n}'\n```\n\nReturns AI-generated answers with sources and images.\n\n### Tavily Extract\n\n```bash\ninfsh app run tavily\u002Fextract --input '{\n  \"urls\": [\"https:\u002F\u002Fexample.com\u002Farticle1\", \"https:\u002F\u002Fexample.com\u002Farticle2\"]\n}'\n```\n\nExtracts clean text and images from multiple URLs.\n\n### Exa Search\n\n```bash\ninfsh app run exa\u002Fsearch --input '{\n  \"query\": \"machine learning frameworks comparison\"\n}'\n```\n\nReturns highly relevant links with context.\n\n### Exa Answer\n\n```bash\ninfsh app run exa\u002Fanswer --input '{\n  \"question\": \"What is the population of Tokyo?\"\n}'\n```\n\nReturns direct factual answers.\n\n### Exa Extract\n\n```bash\ninfsh app run exa\u002Fextract --input '{\n  \"url\": \"https:\u002F\u002Fexample.com\u002Fresearch-paper\"\n}'\n```\n\nExtracts and analyzes web page content.\n\n## Workflow: Research + LLM\n\n```bash\n# 1. Search for information\ninfsh app run tavily\u002Fsearch-assistant --input '{\n  \"query\": \"latest developments in quantum computing\"\n}' > search_results.json\n\n# 2. Analyze with Claude\ninfsh app run openrouter\u002Fclaude-sonnet-45 --input '{\n  \"prompt\": \"Based on this research, summarize the key trends: \u003Csearch-results>\"\n}'\n```\n\n## Workflow: Extract + Summarize\n\n```bash\n# 1. Extract content from URL\ninfsh app run tavily\u002Fextract --input '{\n  \"urls\": [\"https:\u002F\u002Fexample.com\u002Flong-article\"]\n}' > content.json\n\n# 2. Summarize with LLM\ninfsh app run openrouter\u002Fclaude-haiku-45 --input '{\n  \"prompt\": \"Summarize this article in 3 bullet points: \u003Ccontent>\"\n}'\n```\n\n## Use Cases\n\n- **Research**: Gather information on any topic\n- **RAG**: Retrieval-augmented generation\n- **Fact-checking**: Verify claims with sources\n- **Content aggregation**: Collect data from multiple sources\n- **Agents**: Build research-capable AI agents\n\n## Related Skills\n\n```bash\n# Full platform skill (all 150+ apps)\nnpx skills add inference-sh\u002Fagent-skills@inference-sh\n\n# LLM models (combine with search for RAG)\nnpx skills add inference-sh\u002Fagent-skills@llm-models\n\n# Image generation\nnpx skills add inference-sh\u002Fagent-skills@ai-image-generation\n```\n\nBrowse all apps: `infsh app list`\n\n## Documentation\n\n- [Adding Tools to Agents](https:\u002F\u002Finference.sh\u002Fdocs\u002Fagents\u002Fadding-tools) - Equip agents with search\n- [Building a Research Agent](https:\u002F\u002Finference.sh\u002Fblog\u002Fguides\u002Fresearch-agent) - LLM + search integration guide\n- [Tool Integration Tax](https:\u002F\u002Finference.sh\u002Fblog\u002Ftools\u002Fintegration-tax) - Why pre-built tools matter\n","# Web Search & Extraction\n\nSearch the web and extract content via [inference.sh](https:\u002F\u002Finference.sh) CLI.\n\n## Quick Start\n\n```bash\ncurl -fsSL https:\u002F\u002Fcli.inference.sh | sh && infsh login\n\n# Search the web\ninfsh app run tavily\u002Fsearch-assistant --input '{\"query\": \"latest AI developments 2024\"}'\n```\n\n## Available Apps\n\n### Tavily\n\n| App | App ID | Description |\n|-----|--------|-------------|\n| Search Assistant | `tavily\u002Fsearch-assistant` | AI-powered search with answers |\n| Extract | `tavily\u002Fextract` | Extract content from URLs |\n\n### Exa\n\n| App | App ID | Description |\n|-----|--------|-------------|\n| Search | `exa\u002Fsearch` | Smart web search with AI |\n| Answer | `exa\u002Fanswer` | Direct factual answers |\n| Extract | `exa\u002Fextract` | Extract and analyze web content |\n\n## Examples\n\n### Tavily Search\n\n```bash\ninfsh app run tavily\u002Fsearch-assistant --input '{\n  \"query\": \"What are the best practices for building AI agents?\"\n}'\n```\n\nReturns AI-generated answers with sources and images.\n\n### Tavily Extract\n\n```bash\ninfsh app run tavily\u002Fextract --input '{\n  \"urls\": [\"https:\u002F\u002Fexample.com\u002Farticle1\", \"https:\u002F\u002Fexample.com\u002Farticle2\"]\n}'\n```\n\nExtracts clean text and images from multiple URLs.\n\n### Exa Search\n\n```bash\ninfsh app run exa\u002Fsearch --input '{\n  \"query\": \"machine learning frameworks comparison\"\n}'\n```\n\nReturns highly relevant links with context.\n\n### Exa Answer\n\n```bash\ninfsh app run exa\u002Fanswer --input '{\n  \"question\": \"What is the population of Tokyo?\"\n}'\n```\n\nReturns direct factual answers.\n\n### Exa Extract\n\n```bash\ninfsh app run exa\u002Fextract --input '{\n  \"url\": \"https:\u002F\u002Fexample.com\u002Fresearch-paper\"\n}'\n```\n\nExtracts and analyzes web page content.\n\n## Workflow: Research + LLM\n\n```bash\n# 1. Search for information\ninfsh app run tavily\u002Fsearch-assistant --input '{\n  \"query\": \"latest developments in quantum computing\"\n}' > search_results.json\n\n# 2. Analyze with Claude\ninfsh app run openrouter\u002Fclaude-sonnet-45 --input '{\n  \"prompt\": \"Based on this research, summarize the key trends: \u003Csearch-results>\"\n}'\n```\n\n## Workflow: Extract + Summarize\n\n```bash\n# 1. Extract content from URL\ninfsh app run tavily\u002Fextract --input '{\n  \"urls\": [\"https:\u002F\u002Fexample.com\u002Flong-article\"]\n}' > content.json\n\n# 2. Summarize with LLM\ninfsh app run openrouter\u002Fclaude-haiku-45 --input '{\n  \"prompt\": \"Summarize this article in 3 bullet points: \u003Ccontent>\"\n}'\n```\n\n## Use Cases\n\n- **Research**: Gather information on any topic\n- **RAG**: Retrieval-augmented generation\n- **Fact-checking**: Verify claims with sources\n- **Content aggregation**: Collect data from multiple sources\n- **Agents**: Build research-capable AI agents\n\n## Related Skills\n\n```bash\n# Full platform skill (all 150+ apps)\nnpx skills add inference-sh\u002Fagent-skills@inference-sh\n\n# LLM models (combine with search for RAG)\nnpx skills add inference-sh\u002Fagent-skills@llm-models\n\n# Image generation\nnpx skills add inference-sh\u002Fagent-skills@ai-image-generation\n```\n\nBrowse all apps: `infsh app list`\n\n## Documentation\n\n- [Adding Tools to Agents](https:\u002F\u002Finference.sh\u002Fdocs\u002Fagents\u002Fadding-tools) - Equip agents with search\n- [Building a Research Agent](https:\u002F\u002Finference.sh\u002Fblog\u002Fguides\u002Fresearch-agent) - LLM + search integration guide\n- [Tool Integration Tax](https:\u002F\u002Finference.sh\u002Fblog\u002Ftools\u002Fintegration-tax) - Why pre-built tools matter\n",{"name":5,"description":48,"allowed-tools":49},"Web search and content extraction with Tavily and Exa via inference.sh CLI.\nApps: Tavily Search, Tavily Extract, Exa Search, Exa Answer, Exa Extract.\nCapabilities: AI-powered search, content extraction, direct answers, research.\nUse for: research, RAG pipelines, fact-checking, content aggregation, agents.\nTriggers: web search, tavily, exa, search api, content extraction, research,\ninternet search, ai search, search assistant, web scraping, rag, perplexity alternative\n","Bash(infsh *)","main","e7e336ac628c3e3bd771aff1aaa469c93778f94a","skills\u002Fokaris\u002Fweb-search-2",0,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del","2026-08-23 22:39:37",{"source":8,"skillName":5,"commands":58,"prompt":68,"zipAvailable":69},[59,62,65],{"tool":60,"command":61},"npx","npx skills add kbarbel640-del\u002Fskills --skill web-search",{"tool":63,"command":64},"bunx","bunx skills add kbarbel640-del\u002Fskills --skill web-search",{"tool":66,"command":67},"pnpm","pnpm dlx skills add kbarbel640-del\u002Fskills --skill web-search","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fokaris\u002Fweb-search-2\u002FSKILL.md",true,[71],{"path":72,"resourceType":73,"resourceTypeDesc":74,"sizeBytes":75,"sourceHtmlUrl":76},"_meta.json","REFERENCE","参考文档",274,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fokaris\u002Fweb-search-2\u002F_meta.json",[78,107,133,152,158,178],{"skillNo":79,"name":80,"nameZh":6,"description":81,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":82,"categories":83,"keywords":89,"publishedAt":43},"01M6G8J55967D6281ACMKAKTEQ","crowd-prompting","A marketplace where AI agents improve prompts, system instructions, tool descriptions, and other text-based content with domain expertise from real-world operations — and earn tokens for valuable contributions.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzzadrian\u002Fcrowd-prompting\u002FSKILL.md",[84],{"categoryNo":85,"categoryName":86,"taxonomyType":87,"taxonomyTypeDesc":88},"01JBSEEDCAT000000000000036","内容创作者","PROFESSION","适用职业",[90,91,40,30,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106],"crowd prompting","prompting","tokens","domain","world","prompts","operations","instructions","text","tool","system","improve","productivity","marketplace","https","content","ai agents",{"skillNo":108,"name":109,"nameZh":6,"description":110,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":111,"categories":112,"keywords":116,"publishedAt":43},"01M6G8J0PKPAYVET6BWE8W4C26","dilemm-ai","Compete in DilemmAI, the prisoner's dilemma AI arena at dilemm.ai. Use when an OpenClaw agent wants to create an account, design and submit strategy prompts for their bot, enter matchmaking, analyze historical matches and leaderboards, and iterate on bot strategy. Requires headless browser automation (no API available yet).","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzyori\u002Fdilemm-ai\u002FSKILL.md",[113],{"categoryNo":114,"categoryName":115,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发",[117,40,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,95,26],"dilemm ai","arena","analyze","browser","openclaw agent","create","automation","browser automation","bot","openclaw","design","strategy","headless","compete","submit","matchmaking",{"skillNo":134,"name":135,"nameZh":6,"description":136,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":137,"categories":138,"keywords":140,"publishedAt":43},"01M6G8HWAF3K9SW7NP3Z83CPJ6","arxiv-paper-reviews","Interact with arXiv Crawler API to fetch papers, read reviews, and submit comments. Use when working with arXiv papers, fetching paper lists by date\u002Fcategory\u002Finterest, viewing paper details with comments, or submitting paper reviews via API at http:\u002F\u002F150.158.152.82:8000.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzxrys\u002Fweak-accept\u002FSKILL.md",[139],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},[141,142,143,144,145,146,147,30,148,131,26,149,40,150,151],"arxiv paper reviews","reviews","arxiv","paper","crawler","papers","comments","fetch","read","http","via",{"skillNo":153,"name":135,"nameZh":6,"description":136,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":154,"categories":155,"keywords":157,"publishedAt":43},"01M6G8HQJ7N7WMY6YV7D7SSJ16","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzxrys\u002Farxiv-paper-reviews\u002FSKILL.md",[156],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},[144,143,142,141,151,146,147,30,145,131,26,148,149,40,150],{"skillNo":159,"name":160,"nameZh":6,"description":161,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":162,"categories":163,"keywords":164,"publishedAt":43},"01M6G8HM95Y64JNVFC2HN4E2BG","git-summary","Get a quick summary of the current Git repository including status, recent commits, branches, and contributors.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzweack\u002Fgit-summary\u002FSKILL.md",[],[165,166,167,168,169,170,171,172,173,174,175,176,177],"git","summary","git summary","commits","repository","win32","status","linux","contributors","true","quick","get","branches",{"skillNo":179,"name":180,"nameZh":6,"description":181,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":182,"categories":183,"keywords":188,"publishedAt":43},"01M6G8HGEGF05CNEJCGVYFSC4R","agent-constitution","Interact with AgentConstitution governance contracts on Base Sepolia. Check compliance, read rules, log actions, query governance state.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fztsalexey\u002Fagent-constitution\u002FSKILL.md",[184,185],{"categoryNo":114,"categoryName":115,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":186,"categoryName":187,"taxonomyType":87,"taxonomyTypeDesc":88},"01JBSEEDCAT000000000000037","律师与法务",[189,190,191,192,30,193,194,50,195,149,196,197,198,199,200,104,201,202,203],"agent constitution","constitution","contracts","tree","query","base","log","check","Rules","projects","compliance","actions","state","governance","github"]