[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-tavily-threat-intelligence-enrichment":3,"mdc--6avklt-key":36,"related-repo-tavily-threat-intelligence-enrichment":640,"related-org-tavily-threat-intelligence-enrichment":753},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":12,"stars":26,"repoUrl":27,"updatedAt":28,"license":29,"forks":26,"topics":30,"repo":31,"sourceUrl":34,"mdContent":35},"threat-intelligence-enrichment","enrich threat intelligence data","Enrich threat intelligence from CVEs, IOCs, malware names, threat actors, vendor advisories, security incidents, exploit reports, vulnerability disclosures, breach news, and mitigation guidance. Use when the user asks to investigate a CVE, enrich indicators, summarize vendor advisories, assess exploit status, collect mitigations, or produce a source-grounded security brief.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},"tavily","Tavily","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Ftavily.png","tavily-ai",[13,17,20,23],{"name":14,"slug":15,"type":16},"Security","security","tag",{"name":18,"slug":19,"type":16},"Research","research",{"name":21,"slug":22,"type":16},"Threat Modeling","threat-modeling",{"name":24,"slug":25,"type":16},"Code Analysis","code-analysis",0,"https:\u002F\u002Fgithub.com\u002Ftavily-ai\u002Ftavily-grok-plugin","2026-07-21T06:07:30.67376","MIT",[],{"repoUrl":27,"stars":26,"forks":26,"topics":32,"description":33},[],null,"https:\u002F\u002Fgithub.com\u002Ftavily-ai\u002Ftavily-grok-plugin\u002Ftree\u002FHEAD\u002Fskills\u002Fthreat-intelligence-enrichment","---\nname: threat-intelligence-enrichment\ndescription: Enrich threat intelligence from CVEs, IOCs, malware names, threat actors, vendor advisories, security incidents, exploit reports, vulnerability disclosures, breach news, and mitigation guidance. Use when the user asks to investigate a CVE, enrich indicators, summarize vendor advisories, assess exploit status, collect mitigations, or produce a source-grounded security brief.\nlicense: MIT\nmetadata:\n  author: tavily\n  version: \"0.1.0\"\n  homepage: https:\u002F\u002Fwww.tavily.com\n  source: https:\u002F\u002Fgithub.com\u002Ftavily-ai\u002Fuse-case-skills\n---\n\n# Threat Intelligence Enrichment\n\n## Workflow\n\nUse Tavily's MCP search and extract tools to enrich security entities with authoritative and recent evidence; use map or crawl for known vendor portals or advisory collections. Keep this skill focused on query construction, source priority, verification, and security synthesis.\n\nTreat the guidance below as base guidance; adapt it to the user's request when appropriate.\n\n- Identify the input type: CVE, IOC, malware\u002Ftool, threat actor, vendor\u002Fproduct, advisory URL, incident, or campaign.\n- Break the task into short subqueries under 400 characters: identifier, affected product, exploit status, vendor advisory, patches, mitigations, exploitation in the wild, and recent reporting.\n- Search first, using exact-match style queries for CVEs, hashes, domains, IPs, advisory IDs, and malware names.\n- Filter sources before extraction. Prioritize NVD\u002FCVE records, vendor advisories, CISA\u002Fagency alerts, security research blogs, reputable incident reports, and official patch notes.\n- Extract selected pages that can support exploit status, impact, affected versions, mitigations, timeline, or confidence.\n- Use site navigation for vendor advisory portals or documentation sites when the relevant page is hard to find.\n- Collect scoped advisory, changelog, release note, or documentation sections only when the user needs broad coverage.\n\n## Research Budget\n\n- Start with a small focused search set covering the identifier, vendor advisory, exploit status, and mitigation or patch evidence.\n- Extract only the strongest authoritative sources before drafting.\n- Add more searches only for named gaps, such as missing affected versions, missing patch notes, or unclear exploitation status.\n- Do not use map unless a known vendor portal or documentation site has a specific advisory or release note to locate.\n- Do not use crawl unless the user asks for coverage across many related advisories or docs pages.\n\n## Capability Guidance\n\n- Use search for CVEs, IOCs, advisories, exploit status, affected versions, mitigations, and recent incident reporting.\n- Use extract on selected vendor advisories, CVE records, agency alerts, patch notes, and security research pages.\n- Use map when a vendor portal or documentation site is known but the specific advisory is hard to locate.\n- Use crawl for advisory\u002Fdoc sets only when the user asks for coverage across many related pages.\n- Use research only for threat landscape reports or multi-campaign summaries.\n\n## Query And Source Guidance\n\n- Use exact identifiers in queries: CVE IDs, advisory IDs, product\u002Fversion names, hashes, domains, IPs, malware names, and actor aliases.\n- Prioritize vendor advisories, NVD\u002FCVE records, CISA or national agency alerts, CERT\u002FCC, official patch notes, and reputable security research.\n- Treat social posts, exploit-db style references, and secondary news as supporting evidence unless confirmed by authoritative sources.\n- Separate \"exploited in the wild\", \"public PoC\", \"theoretical exploitability\", and \"patched\" as different statuses.\n- Report failed or inaccessible sources when they affect vendor advisories, CVE records, affected-version evidence, or mitigation guidance.\n\n## Output Template\n\nUse this markdown structure and label uncertainty:\n\n```markdown\n# Threat Intelligence Brief: \u003Centity>\n\n## Summary\n- Current status:\n- Confidence:\n- Most important source:\n\n## Entity Details\n- Type:\n- Aliases\u002Fidentifiers:\n- Related products or systems:\n\n## Impact And Exposure\n- Affected products\u002Fversions:\n- Exploit status:\n- Evidence quality:\n\n## Mitigation And Detection\n- Patches or mitigations:\n- Detection or hunting notes:\n- Recommended checks:\n\n## Timeline\n- \u003Cdate>: \u003Cevent> ([source](URL))\n\n## Sources And Gaps\n- Sources:\n- Gaps or unresolved claims:\n```\n\nDo not overstate attribution, exploitation, or compromise evidence. Label speculation and unverified claims.\n",{"data":37,"body":42},{"name":4,"description":6,"license":29,"metadata":38},{"author":8,"version":39,"homepage":40,"source":41},"0.1.0","https:\u002F\u002Fwww.tavily.com","https:\u002F\u002Fgithub.com\u002Ftavily-ai\u002Fuse-case-skills",{"type":43,"children":44},"root",[45,53,60,66,71,111,117,145,151,179,185,213,219,224,629,634],{"type":46,"tag":47,"props":48,"children":49},"element","h1",{"id":4},[50],{"type":51,"value":52},"text","Threat Intelligence Enrichment",{"type":46,"tag":54,"props":55,"children":57},"h2",{"id":56},"workflow",[58],{"type":51,"value":59},"Workflow",{"type":46,"tag":61,"props":62,"children":63},"p",{},[64],{"type":51,"value":65},"Use Tavily's MCP search and extract tools to enrich security entities with authoritative and recent evidence; use map or crawl for known vendor portals or advisory collections. Keep this skill focused on query construction, source priority, verification, and security synthesis.",{"type":46,"tag":61,"props":67,"children":68},{},[69],{"type":51,"value":70},"Treat the guidance below as base guidance; adapt it to the user's request when appropriate.",{"type":46,"tag":72,"props":73,"children":74},"ul",{},[75,81,86,91,96,101,106],{"type":46,"tag":76,"props":77,"children":78},"li",{},[79],{"type":51,"value":80},"Identify the input type: CVE, IOC, malware\u002Ftool, threat actor, vendor\u002Fproduct, advisory URL, incident, or campaign.",{"type":46,"tag":76,"props":82,"children":83},{},[84],{"type":51,"value":85},"Break the task into short subqueries under 400 characters: identifier, affected product, exploit status, vendor advisory, patches, mitigations, exploitation in the wild, and recent reporting.",{"type":46,"tag":76,"props":87,"children":88},{},[89],{"type":51,"value":90},"Search first, using exact-match style queries for CVEs, hashes, domains, IPs, advisory IDs, and malware names.",{"type":46,"tag":76,"props":92,"children":93},{},[94],{"type":51,"value":95},"Filter sources before extraction. Prioritize NVD\u002FCVE records, vendor advisories, CISA\u002Fagency alerts, security research blogs, reputable incident reports, and official patch notes.",{"type":46,"tag":76,"props":97,"children":98},{},[99],{"type":51,"value":100},"Extract selected pages that can support exploit status, impact, affected versions, mitigations, timeline, or confidence.",{"type":46,"tag":76,"props":102,"children":103},{},[104],{"type":51,"value":105},"Use site navigation for vendor advisory portals or documentation sites when the relevant page is hard to find.",{"type":46,"tag":76,"props":107,"children":108},{},[109],{"type":51,"value":110},"Collect scoped advisory, changelog, release note, or documentation sections only when the user needs broad coverage.",{"type":46,"tag":54,"props":112,"children":114},{"id":113},"research-budget",[115],{"type":51,"value":116},"Research 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related advisories or docs pages.",{"type":46,"tag":54,"props":146,"children":148},{"id":147},"capability-guidance",[149],{"type":51,"value":150},"Capability Guidance",{"type":46,"tag":72,"props":152,"children":153},{},[154,159,164,169,174],{"type":46,"tag":76,"props":155,"children":156},{},[157],{"type":51,"value":158},"Use search for CVEs, IOCs, advisories, exploit status, affected versions, mitigations, and recent incident reporting.",{"type":46,"tag":76,"props":160,"children":161},{},[162],{"type":51,"value":163},"Use extract on selected vendor advisories, CVE records, agency alerts, patch notes, and security research pages.",{"type":46,"tag":76,"props":165,"children":166},{},[167],{"type":51,"value":168},"Use map when a vendor portal or documentation site is known but the specific advisory is hard to locate.",{"type":46,"tag":76,"props":170,"children":171},{},[172],{"type":51,"value":173},"Use crawl for advisory\u002Fdoc sets only when the user asks for coverage across many 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Sources:\n",{"type":46,"tag":237,"props":617,"children":619},{"class":239,"line":618},28,[620,624],{"type":46,"tag":237,"props":621,"children":622},{"style":244},[623],{"type":51,"value":302},{"type":46,"tag":237,"props":625,"children":626},{"style":305},[627],{"type":51,"value":628}," Gaps or unresolved claims:\n",{"type":46,"tag":61,"props":630,"children":631},{},[632],{"type":51,"value":633},"Do not overstate attribution, exploitation, or compromise evidence. Label speculation and unverified claims.",{"type":46,"tag":635,"props":636,"children":637},"style",{},[638],{"type":51,"value":639},"html .light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html.light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"items":641,"total":337},[642,659,676,693,712,727,734],{"slug":643,"name":643,"fn":644,"description":645,"org":646,"tags":647,"stars":26,"repoUrl":27,"updatedAt":658},"academic-scientific-research","synthesize academic and scientific literature","Find, screen, and synthesize academic papers, scientific literature, technical reports, preprints, clinical or biomedical publications, and evidence around a research question. Use when the user asks to find papers, summarize literature, compare methods, identify seminal or recent work, extract claims from studies, or build a source-grounded academic\u002Fscientific evidence brief.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[648,651,654,655],{"name":649,"slug":650,"type":16},"Bioinformatics","bioinformatics",{"name":652,"slug":653,"type":16},"Life Sciences","life-sciences",{"name":18,"slug":19,"type":16},{"name":656,"slug":657,"type":16},"Summarization","summarization","2026-07-21T06:07:31.35948",{"slug":660,"name":660,"fn":661,"description":662,"org":663,"tags":664,"stars":26,"repoUrl":27,"updatedAt":675},"investment-research-briefs","create investment research briefs","Create concise investment research briefs, company memos, sector snapshots, portfolio monitoring updates, earnings\u002Fnews summaries, risk and catalyst briefs, and market thesis support. Use when the user asks for an investor-focused brief on a company, sector, public\u002Fprivate market, comparable set, or portfolio theme.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[665,668,671,674],{"name":666,"slug":667,"type":16},"Finance","finance",{"name":669,"slug":670,"type":16},"Financial Modeling","financial-modeling",{"name":672,"slug":673,"type":16},"Investment Banking","investment-banking",{"name":18,"slug":19,"type":16},"2026-07-21T06:07:30.328538",{"slug":677,"name":677,"fn":678,"description":679,"org":680,"tags":681,"stars":26,"repoUrl":27,"updatedAt":692},"product-competitor-intelligence","research competitor products and market data","Research competitor products, SKUs, pricing, packaging, positioning, feature comparisons, product catalogs, category pages, retailer listings, marketplace data, and market intelligence. Use when the user asks for competitor SKU discovery, product data enrichment, pricing\u002Fspec extraction, product comparison, market intelligence, or crawl\u002Fmap-driven product research.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[682,685,688,691],{"name":683,"slug":684,"type":16},"Competitive Intelligence","competitive-intelligence",{"name":686,"slug":687,"type":16},"E-commerce","e-commerce",{"name":689,"slug":690,"type":16},"Marketing","marketing",{"name":18,"slug":19,"type":16},"2026-07-21T06:07:34.257311",{"slug":694,"name":694,"fn":695,"description":696,"org":697,"tags":698,"stars":26,"repoUrl":27,"updatedAt":711},"sales-account-intelligence","build sales account intelligence","Build sales-ready account intelligence for companies, prospects, customers, partners, and target buyers. Use when the user asks for sales prep, account brief, meeting prep, buyer research, expansion signals, customer intelligence, trigger events, executive context, outreach angles, or market\u002Faccount context for GTM teams.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[699,702,705,708],{"name":700,"slug":701,"type":16},"CRM","crm",{"name":703,"slug":704,"type":16},"Lead Enrichment","lead-enrichment",{"name":706,"slug":707,"type":16},"Prospecting","prospecting",{"name":709,"slug":710,"type":16},"Sales","sales","2026-07-21T06:07:33.56804",{"slug":713,"name":713,"fn":714,"description":715,"org":716,"tags":717,"stars":26,"repoUrl":27,"updatedAt":726},"tavily-web","research the web with Tavily","Search and research the web with Tavily. Use for current information, source discovery, webpage extraction, site mapping, documentation crawling, comparisons, and comprehensive research with citations.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[718,719,722,723],{"name":18,"slug":19,"type":16},{"name":720,"slug":721,"type":16},"Search","search",{"name":9,"slug":8,"type":16},{"name":724,"slug":725,"type":16},"Web Scraping","web-scraping","2026-07-21T06:07:29.989683",{"slug":4,"name":4,"fn":5,"description":6,"org":728,"tags":729,"stars":26,"repoUrl":27,"updatedAt":28},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[730,731,732,733],{"name":24,"slug":25,"type":16},{"name":18,"slug":19,"type":16},{"name":14,"slug":15,"type":16},{"name":21,"slug":22,"type":16},{"slug":735,"name":735,"fn":736,"description":737,"org":738,"tags":739,"stars":26,"repoUrl":27,"updatedAt":752},"vendor-risk-kyc-screening","screen vendors for risk and compliance","Screen vendors, merchants, suppliers, counterparties, companies, executives, and related entities for vendor risk, KYC, adverse media, sanctions, regulatory actions, litigation, recalls, supplier risk, cybersecurity incidents, and compliance concerns. Use when the user asks for vendor onboarding research, KYC screening, supplier due diligence, merchant case research, or a source-grounded risk brief.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[740,743,746,749],{"name":741,"slug":742,"type":16},"Compliance","compliance",{"name":744,"slug":745,"type":16},"KYC","kyc",{"name":747,"slug":748,"type":16},"Risk Assessment","risk-assessment",{"name":750,"slug":751,"type":16},"Vendor Management","vendor-management","2026-07-21T06:07:33.917725",{"items":754,"total":444},[755,769,782,795,805,818,829,840,853,860,867,874],{"slug":756,"name":756,"fn":757,"description":758,"org":759,"tags":760,"stars":766,"repoUrl":767,"updatedAt":768},"tavily-best-practices","implement Tavily integration best practices","Build production-ready Tavily integrations with best practices baked in. Reference documentation for developers using coding assistants (Claude Code, Cursor, etc.) to implement web search, content extraction, crawling, and research in agentic workflows, RAG systems, or autonomous agents.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[761,764,765],{"name":762,"slug":763,"type":16},"API Development","api-development",{"name":720,"slug":721,"type":16},{"name":9,"slug":8,"type":16},426,"https:\u002F\u002Fgithub.com\u002Ftavily-ai\u002Fskills","2026-04-06T18:54:03.550741",{"slug":770,"name":770,"fn":771,"description":772,"org":773,"tags":774,"stars":766,"repoUrl":767,"updatedAt":781},"tavily-cli","conduct web research with Tavily CLI","Web search, content extraction, crawling, and deep research via the Tavily CLI. Use this skill whenever the user wants to search the web, find articles, research a topic, look something up online, extract content from a URL, grab text from a webpage, crawl documentation, download a site's pages, discover URLs on a domain, or conduct in-depth research with citations. Also use when they say \"fetch this page\", \"pull the content from\", \"get the page at https:\u002F\u002F\", \"find me articles about\", or reference extracting data from external websites. This provides LLM-optimized web search, content extraction, site crawling, URL discovery, and AI-powered deep research — capabilities beyond what agents can do natively. Do NOT trigger for local file operations, git commands, deployments, or code editing tasks.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[775,778,779,780],{"name":776,"slug":777,"type":16},"CLI","cli",{"name":18,"slug":19,"type":16},{"name":720,"slug":721,"type":16},{"name":9,"slug":8,"type":16},"2026-04-06T18:54:02.065814",{"slug":783,"name":783,"fn":784,"description":785,"org":786,"tags":787,"stars":766,"repoUrl":767,"updatedAt":794},"tavily-crawl","crawl websites and extract content","Crawl websites and extract content from multiple pages via the Tavily CLI. Use this skill when the user wants to crawl a site, download documentation, extract an entire docs section, bulk-extract pages, save a site as local markdown files, or says \"crawl\", \"get all the pages\", \"download the docs\", \"extract everything under \u002Fdocs\", \"bulk extract\", or needs content from many pages on the same domain. Supports depth\u002Fbreadth control, path filtering, semantic instructions, and saving each page as a local markdown file.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[788,791,792,793],{"name":789,"slug":790,"type":16},"Automation","automation",{"name":776,"slug":777,"type":16},{"name":9,"slug":8,"type":16},{"name":724,"slug":725,"type":16},"2026-04-06T18:54:09.921446",{"slug":796,"name":796,"fn":797,"description":798,"org":799,"tags":800,"stars":766,"repoUrl":767,"updatedAt":804},"tavily-dynamic-search","search the web via Tavily","Programmatic web search with context isolation. Use this skill for any research task where you need to search the web, filter results, and extract specific information — without polluting your context window with raw HTML and boilerplate. This is the default skill for web research. Triggered by \"search for\", \"look up\", \"find\", \"research\", \"what's the latest on\", or any query that requires current web information. Also use when asked to \"search and filter\", \"find the important parts\", or \"extract the key details\" — any case where the user wants curated, noise-free content.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[801,802,803],{"name":18,"slug":19,"type":16},{"name":720,"slug":721,"type":16},{"name":9,"slug":8,"type":16},"2026-04-14T04:50:31.944584",{"slug":806,"name":806,"fn":807,"description":808,"org":809,"tags":810,"stars":766,"repoUrl":767,"updatedAt":817},"tavily-extract","extract markdown content from URLs","Extract clean markdown or text content from specific URLs via the Tavily CLI. Use this skill when the user has one or more URLs and wants their content, says \"extract\", \"grab the content from\", \"pull the text from\", \"get the page at\", \"read this webpage\", or needs clean text from web pages. Handles JavaScript-rendered pages, returns LLM-optimized markdown, and supports query-focused chunking for targeted extraction. Can process up to 20 URLs in a single call.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[811,812,815,816],{"name":776,"slug":777,"type":16},{"name":813,"slug":814,"type":16},"Content Creation","content-creation",{"name":9,"slug":8,"type":16},{"name":724,"slug":725,"type":16},"2026-04-06T18:54:08.624436",{"slug":819,"name":819,"fn":820,"description":821,"org":822,"tags":823,"stars":766,"repoUrl":767,"updatedAt":828},"tavily-map","map website URLs with Tavily","Discover and list all URLs on a website without extracting content, via the Tavily CLI. Use this skill when the user wants to find a specific page on a large site, list all URLs, see the site structure, find where something is on a domain, or says \"map the site\", \"find the URL for\", \"what pages are on\", \"list all pages\", or \"site structure\". Faster than crawling — returns URLs only. Essential when you know the site but not the exact page. Combine with extract for targeted content retrieval.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[824,825,826,827],{"name":776,"slug":777,"type":16},{"name":720,"slug":721,"type":16},{"name":9,"slug":8,"type":16},{"name":724,"slug":725,"type":16},"2026-04-06T18:54:04.832149",{"slug":830,"name":830,"fn":831,"description":832,"org":833,"tags":834,"stars":766,"repoUrl":767,"updatedAt":839},"tavily-research","conduct AI-powered research with Tavily","Conduct comprehensive AI-powered research with citations via the Tavily CLI. Use this skill when the user wants deep research, a detailed report, a comparison, market analysis, literature review, or says \"research\", \"investigate\", \"analyze in depth\", \"compare X vs Y\", \"what does the market look like for\", or needs multi-source synthesis with explicit citations. Returns a structured report grounded in web sources. Takes 30-120 seconds. For quick fact-finding, use tavily-search instead.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[835,836,837,838],{"name":776,"slug":777,"type":16},{"name":18,"slug":19,"type":16},{"name":656,"slug":657,"type":16},{"name":9,"slug":8,"type":16},"2026-04-06T18:54:07.378619",{"slug":841,"name":841,"fn":842,"description":843,"org":844,"tags":845,"stars":766,"repoUrl":767,"updatedAt":852},"tavily-search","search the web with Tavily","Search the web with LLM-optimized results via the Tavily CLI. Use this skill when the user wants to search the web, find articles, look up information, get recent news, discover sources, or says \"search for\", \"find me\", \"look up\", \"what's the latest on\", \"find articles about\", or needs current information from the internet. Returns relevant results with content snippets, relevance scores, and metadata — optimized for LLM consumption. Supports domain filtering, time ranges, and multiple search depths.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[846,847,850,851],{"name":776,"slug":777,"type":16},{"name":848,"slug":849,"type":16},"LLM","llm",{"name":720,"slug":721,"type":16},{"name":9,"slug":8,"type":16},"2026-04-06T18:54:06.085596",{"slug":643,"name":643,"fn":644,"description":645,"org":854,"tags":855,"stars":26,"repoUrl":27,"updatedAt":658},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[856,857,858,859],{"name":649,"slug":650,"type":16},{"name":652,"slug":653,"type":16},{"name":18,"slug":19,"type":16},{"name":656,"slug":657,"type":16},{"slug":660,"name":660,"fn":661,"description":662,"org":861,"tags":862,"stars":26,"repoUrl":27,"updatedAt":675},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[863,864,865,866],{"name":666,"slug":667,"type":16},{"name":669,"slug":670,"type":16},{"name":672,"slug":673,"type":16},{"name":18,"slug":19,"type":16},{"slug":677,"name":677,"fn":678,"description":679,"org":868,"tags":869,"stars":26,"repoUrl":27,"updatedAt":692},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[870,871,872,873],{"name":683,"slug":684,"type":16},{"name":686,"slug":687,"type":16},{"name":689,"slug":690,"type":16},{"name":18,"slug":19,"type":16},{"slug":694,"name":694,"fn":695,"description":696,"org":875,"tags":876,"stars":26,"repoUrl":27,"updatedAt":711},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[877,878,879,880],{"name":700,"slug":701,"type":16},{"name":703,"slug":704,"type":16},{"name":706,"slug":707,"type":16},{"name":709,"slug":710,"type":16}]