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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},"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},"Research","research","tag",{"name":18,"slug":19,"type":16},"Summarization","summarization",{"name":21,"slug":22,"type":16},"Life Sciences","life-sciences",{"name":24,"slug":25,"type":16},"Bioinformatics","bioinformatics",0,"https:\u002F\u002Fgithub.com\u002Ftavily-ai\u002Ftavily-grok-plugin","2026-07-21T06:07:31.35948","MIT",[],{"repoUrl":27,"stars":26,"forks":26,"topics":32,"description":33},[],null,"https:\u002F\u002Fgithub.com\u002Ftavily-ai\u002Ftavily-grok-plugin\u002Ftree\u002FHEAD\u002Fskills\u002Facademic-scientific-research","---\nname: academic-scientific-research\ndescription: 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.\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# Academic Scientific Research\n\n## Workflow\n\nUse Tavily's MCP tools to search for scholarly sources, extract and verify source content, map or crawl known scholarly sites and collections, and run full literature-review research. Keep this skill focused on research planning, source selection, extraction targets, and evidence synthesis.\n\nTreat the guidance below as base guidance; adapt it to the user's request when appropriate.\n\n- Translate the user's question into search terms, synonyms, key entities, and likely source domains.\n- Break broad questions into short subqueries under 400 characters: core concept, synonyms, method names, target population or data, benchmark or dataset, author\u002Flab, and year range.\n- Prefer scholarly and official sources when available: preprint servers, PubMed\u002FNIH pages, journals, conference proceedings, professional societies, standards bodies, and official technical reports.\n- Extract from the strongest selected pages after screening titles, snippets, source type, recency, and relevance.\n- Reserve broad research synthesis for full literature reviews, research landscapes, or multi-method comparisons.\n- Distinguish primary studies, review papers, preprints, editorials, guidelines, standards, and news coverage.\n\n## Research Budget\n\n- Start with a small focused search set covering the main concept, synonyms, methods, and source type.\n- Extract only the strongest scholarly sources before drafting the evidence brief.\n- Add more searches only for named gaps, such as missing review papers, missing recent work, or missing primary studies.\n- Do not use map unless a known lab, journal, conference, repository, or documentation site has buried pages.\n- Do not use crawl unless the user needs broad collection from a known proceedings, publication list, or docs section.\n\n## Capability Guidance\n\n- Use search first when the user needs papers, methods, benchmarks, authors, institutions, or recent work.\n- Use extract when comparing a small set of papers, reading abstracts, or verifying study claims.\n- Use map only when a known lab, journal, conference, repository, or documentation site has useful but hard-to-find pages.\n- Use crawl only when the user needs many pages from a known source, such as proceedings, a lab publication list, or a technical docs section.\n- Use research only when the user explicitly needs a full literature review or research landscape.\n\n## Query And Source Guidance\n\n- Pair formal terms with common synonyms and acronyms.\n- Include population, dataset, benchmark, organism, intervention, model, metric, or method terms when relevant.\n- For recent literature, include explicit year ranges or recency language in the query.\n- Prefer primary literature for claims, review papers for landscape summaries, and guidelines\u002Fstandards for practice recommendations.\n- Deduplicate preprints and final publications; cite the final version when available.\n- Treat abstracts, papers, supplemental pages, tables, and official repositories as separate evidence surfaces.\n- Report failed or inaccessible sources when they affect key papers, guidelines, datasets, or primary evidence.\n\n## Output Template\n\nUse this markdown structure and adapt sections to the user's scope:\n\n```markdown\n# Evidence Brief: \u003Ctopic>\n\n## Research Question\n\u003Cbrief framing of the question>\n\n## Search Strategy\n- Concepts searched:\n- Source types prioritized:\n- Inclusion logic:\n- Exclusions or limitations:\n\n## Key Sources\n| Source | Type | Why it matters | URL |\n| --- | --- | --- | --- |\n\n## Findings\n### \u003CTheme>\n- Claim:\n- Evidence:\n- Limitations:\n\n### \u003CTheme>\n- Claim:\n- Evidence:\n- Limitations:\n\n## Consensus And Disagreement\n- Consensus:\n- Disagreement:\n- Evidence gaps:\n\n## Follow-Up Queries\n- \u003Cquery idea>\n```\n\nFor medical, clinical, or biomedical topics, be conservative: do not provide diagnosis or treatment advice, and prioritize primary literature, systematic reviews, guidelines, and official health sources.\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",[45,53,60,66,71,106,112,140,146,174,180,218,224,229,632,637],{"type":46,"tag":47,"props":48,"children":49},"element","h1",{"id":4},[50],{"type":51,"value":52},"text","Academic Scientific Research",{"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 tools to search for scholarly sources, extract and verify source content, map or crawl known scholarly sites and collections, and run full literature-review research. 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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":644,"total":357},[645,652,669,686,705,720,737],{"slug":4,"name":4,"fn":5,"description":6,"org":646,"tags":647,"stars":26,"repoUrl":27,"updatedAt":28},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[648,649,650,651],{"name":24,"slug":25,"type":16},{"name":21,"slug":22,"type":16},{"name":14,"slug":15,"type":16},{"name":18,"slug":19,"type":16},{"slug":653,"name":653,"fn":654,"description":655,"org":656,"tags":657,"stars":26,"repoUrl":27,"updatedAt":668},"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},[658,661,664,667],{"name":659,"slug":660,"type":16},"Finance","finance",{"name":662,"slug":663,"type":16},"Financial Modeling","financial-modeling",{"name":665,"slug":666,"type":16},"Investment Banking","investment-banking",{"name":14,"slug":15,"type":16},"2026-07-21T06:07:30.328538",{"slug":670,"name":670,"fn":671,"description":672,"org":673,"tags":674,"stars":26,"repoUrl":27,"updatedAt":685},"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},[675,678,681,684],{"name":676,"slug":677,"type":16},"Competitive Intelligence","competitive-intelligence",{"name":679,"slug":680,"type":16},"E-commerce","e-commerce",{"name":682,"slug":683,"type":16},"Marketing","marketing",{"name":14,"slug":15,"type":16},"2026-07-21T06:07:34.257311",{"slug":687,"name":687,"fn":688,"description":689,"org":690,"tags":691,"stars":26,"repoUrl":27,"updatedAt":704},"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},[692,695,698,701],{"name":693,"slug":694,"type":16},"CRM","crm",{"name":696,"slug":697,"type":16},"Lead Enrichment","lead-enrichment",{"name":699,"slug":700,"type":16},"Prospecting","prospecting",{"name":702,"slug":703,"type":16},"Sales","sales","2026-07-21T06:07:33.56804",{"slug":706,"name":706,"fn":707,"description":708,"org":709,"tags":710,"stars":26,"repoUrl":27,"updatedAt":719},"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},[711,712,715,716],{"name":14,"slug":15,"type":16},{"name":713,"slug":714,"type":16},"Search","search",{"name":9,"slug":8,"type":16},{"name":717,"slug":718,"type":16},"Web Scraping","web-scraping","2026-07-21T06:07:29.989683",{"slug":721,"name":721,"fn":722,"description":723,"org":724,"tags":725,"stars":26,"repoUrl":27,"updatedAt":736},"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},[726,729,730,733],{"name":727,"slug":728,"type":16},"Code Analysis","code-analysis",{"name":14,"slug":15,"type":16},{"name":731,"slug":732,"type":16},"Security","security",{"name":734,"slug":735,"type":16},"Threat Modeling","threat-modeling","2026-07-21T06:07:30.67376",{"slug":738,"name":738,"fn":739,"description":740,"org":741,"tags":742,"stars":26,"repoUrl":27,"updatedAt":755},"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},[743,746,749,752],{"name":744,"slug":745,"type":16},"Compliance","compliance",{"name":747,"slug":748,"type":16},"KYC","kyc",{"name":750,"slug":751,"type":16},"Risk Assessment","risk-assessment",{"name":753,"slug":754,"type":16},"Vendor Management","vendor-management","2026-07-21T06:07:33.917725",{"items":757,"total":436},[758,772,785,798,808,821,832,843,856,863,870,877],{"slug":759,"name":759,"fn":760,"description":761,"org":762,"tags":763,"stars":769,"repoUrl":770,"updatedAt":771},"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},[764,767,768],{"name":765,"slug":766,"type":16},"API Development","api-development",{"name":713,"slug":714,"type":16},{"name":9,"slug":8,"type":16},426,"https:\u002F\u002Fgithub.com\u002Ftavily-ai\u002Fskills","2026-04-06T18:54:03.550741",{"slug":773,"name":773,"fn":774,"description":775,"org":776,"tags":777,"stars":769,"repoUrl":770,"updatedAt":784},"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},[778,781,782,783],{"name":779,"slug":780,"type":16},"CLI","cli",{"name":14,"slug":15,"type":16},{"name":713,"slug":714,"type":16},{"name":9,"slug":8,"type":16},"2026-04-06T18:54:02.065814",{"slug":786,"name":786,"fn":787,"description":788,"org":789,"tags":790,"stars":769,"repoUrl":770,"updatedAt":797},"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},[791,794,795,796],{"name":792,"slug":793,"type":16},"Automation","automation",{"name":779,"slug":780,"type":16},{"name":9,"slug":8,"type":16},{"name":717,"slug":718,"type":16},"2026-04-06T18:54:09.921446",{"slug":799,"name":799,"fn":800,"description":801,"org":802,"tags":803,"stars":769,"repoUrl":770,"updatedAt":807},"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},[804,805,806],{"name":14,"slug":15,"type":16},{"name":713,"slug":714,"type":16},{"name":9,"slug":8,"type":16},"2026-04-14T04:50:31.944584",{"slug":809,"name":809,"fn":810,"description":811,"org":812,"tags":813,"stars":769,"repoUrl":770,"updatedAt":820},"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},[814,815,818,819],{"name":779,"slug":780,"type":16},{"name":816,"slug":817,"type":16},"Content Creation","content-creation",{"name":9,"slug":8,"type":16},{"name":717,"slug":718,"type":16},"2026-04-06T18:54:08.624436",{"slug":822,"name":822,"fn":823,"description":824,"org":825,"tags":826,"stars":769,"repoUrl":770,"updatedAt":831},"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},[827,828,829,830],{"name":779,"slug":780,"type":16},{"name":713,"slug":714,"type":16},{"name":9,"slug":8,"type":16},{"name":717,"slug":718,"type":16},"2026-04-06T18:54:04.832149",{"slug":833,"name":833,"fn":834,"description":835,"org":836,"tags":837,"stars":769,"repoUrl":770,"updatedAt":842},"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},[838,839,840,841],{"name":779,"slug":780,"type":16},{"name":14,"slug":15,"type":16},{"name":18,"slug":19,"type":16},{"name":9,"slug":8,"type":16},"2026-04-06T18:54:07.378619",{"slug":844,"name":844,"fn":845,"description":846,"org":847,"tags":848,"stars":769,"repoUrl":770,"updatedAt":855},"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},[849,850,853,854],{"name":779,"slug":780,"type":16},{"name":851,"slug":852,"type":16},"LLM","llm",{"name":713,"slug":714,"type":16},{"name":9,"slug":8,"type":16},"2026-04-06T18:54:06.085596",{"slug":4,"name":4,"fn":5,"description":6,"org":857,"tags":858,"stars":26,"repoUrl":27,"updatedAt":28},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[859,860,861,862],{"name":24,"slug":25,"type":16},{"name":21,"slug":22,"type":16},{"name":14,"slug":15,"type":16},{"name":18,"slug":19,"type":16},{"slug":653,"name":653,"fn":654,"description":655,"org":864,"tags":865,"stars":26,"repoUrl":27,"updatedAt":668},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[866,867,868,869],{"name":659,"slug":660,"type":16},{"name":662,"slug":663,"type":16},{"name":665,"slug":666,"type":16},{"name":14,"slug":15,"type":16},{"slug":670,"name":670,"fn":671,"description":672,"org":871,"tags":872,"stars":26,"repoUrl":27,"updatedAt":685},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[873,874,875,876],{"name":676,"slug":677,"type":16},{"name":679,"slug":680,"type":16},{"name":682,"slug":683,"type":16},{"name":14,"slug":15,"type":16},{"slug":687,"name":687,"fn":688,"description":689,"org":878,"tags":879,"stars":26,"repoUrl":27,"updatedAt":704},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[880,881,882,883],{"name":693,"slug":694,"type":16},{"name":696,"slug":697,"type":16},{"name":699,"slug":700,"type":16},{"name":702,"slug":703,"type":16}]