[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-tavily-investment-research-briefs":3,"mdc--73s4zh-key":36,"related-repo-tavily-investment-research-briefs":630,"related-org-tavily-investment-research-briefs":743},{"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},"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. 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Use when the user asks for an investor-focused brief on a company, sector, public\u002Fprivate market, comparable set, or portfolio theme.\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# Investment Research Briefs\n\n## Workflow\n\nUse Tavily's MCP search and extract tools for quick investor briefs and source checks, research for full investment memos, and map or crawl only for large known source collections. Keep this skill focused on research design, source selection, verification, and synthesis.\n\nTreat the guidance below as base guidance; adapt it to the user's request when appropriate.\n\n- Define the target, investor lens, geography, timeframe, asset type, and desired depth.\n- For quick briefs, split into short subqueries under 400 characters: business overview, market position, financial\u002Foperating signals, recent developments, competitors, risks, catalysts, and valuation\u002Fcomps if requested.\n- Prefer filings, investor relations pages, earnings materials, company pages, regulators, exchanges, reputable financial media, and market sources.\n- For deeper memos, provide a clear research goal, known context, constraints, target market, and desired output shape.\n- Verify specific metrics, quotes, management claims, filings, and high-impact assertions against original or authoritative sources.\n- Separate sourced facts, inferred interpretation, and open diligence questions.\n\n## Research Budget\n\n- Start with a small focused search set covering business context, recent developments, financial\u002Foperating signals, and risks\u002Fcatalysts.\n- Extract only the strongest sources before drafting a concise brief.\n- Add more searches only for named gaps, such as missing filing evidence, missing earnings context, or missing competitor context.\n- Do not use map unless a known investor-relations, filing, transcript, or presentation library has buried pages.\n- Do not use research unless the user asks for a full memo, sector landscape, or multi-source thesis.\n\n## Capability Guidance\n\n- Use search for fast discovery across companies, sectors, filings, news, competitors, and market context.\n- Use extract to verify metrics, quotes, filings, management claims, transcripts, and other high-impact assertions.\n- Use research for full investment memos, sector landscapes, or multi-source thesis work.\n- Use map or crawl only for large investor-relations, filing, transcript, or presentation libraries.\n\n## Query And Source Guidance\n\n- Use company legal name, ticker, product names, segment names, geography, competitor names, and reporting period in queries.\n- For public companies, prioritize original filings, earnings calls, investor presentations, regulator pages, and exchange notices.\n- For private companies, triangulate from company pages, funding announcements, customer stories, hiring, product documentation, and credible press.\n- For recent developments, make the timeframe explicit in the query.\n- For competitor or sector work, build separate subqueries for category, demand drivers, pricing, regulation, customer adoption, and risks.\n- Include known assumptions or prior context in broad research requests to avoid rediscovering what is already known.\n- Report failed or unavailable sources when they affect filings, transcripts, IR pages, market data, or cited claims.\n\n## Output Template\n\nUse this markdown structure and adapt sections to the user's mandate:\n\n```markdown\n# Investment Brief: \u003Ccompany\u002Fsector\u002Ftheme>\n\n## Executive Summary\n\u003Cconcise bullets with the main investor-relevant takeaways>\n\n## Business And Market Context\n- Business model:\n- Customers\u002Fsegments:\n- Market position:\n- Competitors:\n\n## Recent Developments\n- \u003Cdated development with source>\n\n## Signals\n- Financial or operating signals:\n- Product, customer, hiring, or partnership signals:\n- Regulatory or macro signals:\n\n## Risks\n- \u003Crisk>: \u003Cevidence and uncertainty>\n\n## Catalysts And Watch Items\n- \u003Ccatalyst\u002Fwatch item>: \u003Cwhy it matters>\n\n## Open Diligence Questions\n- \u003Cquestion>\n\n## Sources\n- [Source title](URL) - \u003Cwhat it supports>\n```\n\nDo not provide personalized financial advice. State when source coverage is thin, stale, or incomplete.\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",[45,53,60,66,71,106,112,140,146,169,175,213,219,224,619,624],{"type":46,"tag":47,"props":48,"children":49},"element","h1",{"id":4},[50],{"type":51,"value":52},"text","Investment Research Briefs",{"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 for quick investor briefs and source checks, research for full investment memos, and map or crawl only for large known source collections. Keep this skill focused on research design, source selection, verification, and 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],{"type":46,"tag":76,"props":77,"children":78},"li",{},[79],{"type":51,"value":80},"Define the target, investor lens, geography, timeframe, asset type, and desired depth.",{"type":46,"tag":76,"props":82,"children":83},{},[84],{"type":51,"value":85},"For quick briefs, split into short subqueries under 400 characters: business overview, market position, financial\u002Foperating signals, recent developments, competitors, risks, catalysts, and valuation\u002Fcomps if requested.",{"type":46,"tag":76,"props":87,"children":88},{},[89],{"type":51,"value":90},"Prefer filings, investor relations pages, earnings materials, company pages, regulators, exchanges, 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title",{"type":46,"tag":237,"props":599,"children":600},{"style":244},[601],{"type":51,"value":602},"](",{"type":46,"tag":237,"props":604,"children":606},{"style":605},"--shiki-light:#E53935;--shiki-light-text-decoration:underline;--shiki-default:#F07178;--shiki-default-text-decoration:underline;--shiki-dark:#F07178;--shiki-dark-text-decoration:underline",[607],{"type":51,"value":608},"URL",{"type":46,"tag":237,"props":610,"children":611},{"style":244},[612],{"type":51,"value":613},")",{"type":46,"tag":237,"props":615,"children":616},{"style":284},[617],{"type":51,"value":618}," - \u003Cwhat it supports>\n",{"type":46,"tag":61,"props":620,"children":621},{},[622],{"type":51,"value":623},"Do not provide personalized financial advice. State when source coverage is thin, stale, or incomplete.",{"type":46,"tag":625,"props":626,"children":627},"style",{},[628],{"type":51,"value":629},"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":631,"total":311},[632,649,656,673,692,707,724],{"slug":633,"name":633,"fn":634,"description":635,"org":636,"tags":637,"stars":26,"repoUrl":27,"updatedAt":648},"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},[638,641,644,645],{"name":639,"slug":640,"type":16},"Bioinformatics","bioinformatics",{"name":642,"slug":643,"type":16},"Life Sciences","life-sciences",{"name":14,"slug":15,"type":16},{"name":646,"slug":647,"type":16},"Summarization","summarization","2026-07-21T06:07:31.35948",{"slug":4,"name":4,"fn":5,"description":6,"org":650,"tags":651,"stars":26,"repoUrl":27,"updatedAt":28},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[652,653,654,655],{"name":21,"slug":22,"type":16},{"name":18,"slug":19,"type":16},{"name":24,"slug":25,"type":16},{"name":14,"slug":15,"type":16},{"slug":657,"name":657,"fn":658,"description":659,"org":660,"tags":661,"stars":26,"repoUrl":27,"updatedAt":672},"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},[662,665,668,671],{"name":663,"slug":664,"type":16},"Competitive Intelligence","competitive-intelligence",{"name":666,"slug":667,"type":16},"E-commerce","e-commerce",{"name":669,"slug":670,"type":16},"Marketing","marketing",{"name":14,"slug":15,"type":16},"2026-07-21T06:07:34.257311",{"slug":674,"name":674,"fn":675,"description":676,"org":677,"tags":678,"stars":26,"repoUrl":27,"updatedAt":691},"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},[679,682,685,688],{"name":680,"slug":681,"type":16},"CRM","crm",{"name":683,"slug":684,"type":16},"Lead Enrichment","lead-enrichment",{"name":686,"slug":687,"type":16},"Prospecting","prospecting",{"name":689,"slug":690,"type":16},"Sales","sales","2026-07-21T06:07:33.56804",{"slug":693,"name":693,"fn":694,"description":695,"org":696,"tags":697,"stars":26,"repoUrl":27,"updatedAt":706},"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},[698,699,702,703],{"name":14,"slug":15,"type":16},{"name":700,"slug":701,"type":16},"Search","search",{"name":9,"slug":8,"type":16},{"name":704,"slug":705,"type":16},"Web Scraping","web-scraping","2026-07-21T06:07:29.989683",{"slug":708,"name":708,"fn":709,"description":710,"org":711,"tags":712,"stars":26,"repoUrl":27,"updatedAt":723},"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},[713,716,717,720],{"name":714,"slug":715,"type":16},"Code Analysis","code-analysis",{"name":14,"slug":15,"type":16},{"name":718,"slug":719,"type":16},"Security","security",{"name":721,"slug":722,"type":16},"Threat Modeling","threat-modeling","2026-07-21T06:07:30.67376",{"slug":725,"name":725,"fn":726,"description":727,"org":728,"tags":729,"stars":26,"repoUrl":27,"updatedAt":742},"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},[730,733,736,739],{"name":731,"slug":732,"type":16},"Compliance","compliance",{"name":734,"slug":735,"type":16},"KYC","kyc",{"name":737,"slug":738,"type":16},"Risk Assessment","risk-assessment",{"name":740,"slug":741,"type":16},"Vendor Management","vendor-management","2026-07-21T06:07:33.917725",{"items":744,"total":419},[745,759,772,785,795,808,819,830,843,850,857,864],{"slug":746,"name":746,"fn":747,"description":748,"org":749,"tags":750,"stars":756,"repoUrl":757,"updatedAt":758},"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},[751,754,755],{"name":752,"slug":753,"type":16},"API Development","api-development",{"name":700,"slug":701,"type":16},{"name":9,"slug":8,"type":16},426,"https:\u002F\u002Fgithub.com\u002Ftavily-ai\u002Fskills","2026-04-06T18:54:03.550741",{"slug":760,"name":760,"fn":761,"description":762,"org":763,"tags":764,"stars":756,"repoUrl":757,"updatedAt":771},"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},[765,768,769,770],{"name":766,"slug":767,"type":16},"CLI","cli",{"name":14,"slug":15,"type":16},{"name":700,"slug":701,"type":16},{"name":9,"slug":8,"type":16},"2026-04-06T18:54:02.065814",{"slug":773,"name":773,"fn":774,"description":775,"org":776,"tags":777,"stars":756,"repoUrl":757,"updatedAt":784},"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},[778,781,782,783],{"name":779,"slug":780,"type":16},"Automation","automation",{"name":766,"slug":767,"type":16},{"name":9,"slug":8,"type":16},{"name":704,"slug":705,"type":16},"2026-04-06T18:54:09.921446",{"slug":786,"name":786,"fn":787,"description":788,"org":789,"tags":790,"stars":756,"repoUrl":757,"updatedAt":794},"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},[791,792,793],{"name":14,"slug":15,"type":16},{"name":700,"slug":701,"type":16},{"name":9,"slug":8,"type":16},"2026-04-14T04:50:31.944584",{"slug":796,"name":796,"fn":797,"description":798,"org":799,"tags":800,"stars":756,"repoUrl":757,"updatedAt":807},"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},[801,802,805,806],{"name":766,"slug":767,"type":16},{"name":803,"slug":804,"type":16},"Content Creation","content-creation",{"name":9,"slug":8,"type":16},{"name":704,"slug":705,"type":16},"2026-04-06T18:54:08.624436",{"slug":809,"name":809,"fn":810,"description":811,"org":812,"tags":813,"stars":756,"repoUrl":757,"updatedAt":818},"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},[814,815,816,817],{"name":766,"slug":767,"type":16},{"name":700,"slug":701,"type":16},{"name":9,"slug":8,"type":16},{"name":704,"slug":705,"type":16},"2026-04-06T18:54:04.832149",{"slug":820,"name":820,"fn":821,"description":822,"org":823,"tags":824,"stars":756,"repoUrl":757,"updatedAt":829},"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},[825,826,827,828],{"name":766,"slug":767,"type":16},{"name":14,"slug":15,"type":16},{"name":646,"slug":647,"type":16},{"name":9,"slug":8,"type":16},"2026-04-06T18:54:07.378619",{"slug":831,"name":831,"fn":832,"description":833,"org":834,"tags":835,"stars":756,"repoUrl":757,"updatedAt":842},"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},[836,837,840,841],{"name":766,"slug":767,"type":16},{"name":838,"slug":839,"type":16},"LLM","llm",{"name":700,"slug":701,"type":16},{"name":9,"slug":8,"type":16},"2026-04-06T18:54:06.085596",{"slug":633,"name":633,"fn":634,"description":635,"org":844,"tags":845,"stars":26,"repoUrl":27,"updatedAt":648},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[846,847,848,849],{"name":639,"slug":640,"type":16},{"name":642,"slug":643,"type":16},{"name":14,"slug":15,"type":16},{"name":646,"slug":647,"type":16},{"slug":4,"name":4,"fn":5,"description":6,"org":851,"tags":852,"stars":26,"repoUrl":27,"updatedAt":28},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[853,854,855,856],{"name":21,"slug":22,"type":16},{"name":18,"slug":19,"type":16},{"name":24,"slug":25,"type":16},{"name":14,"slug":15,"type":16},{"slug":657,"name":657,"fn":658,"description":659,"org":858,"tags":859,"stars":26,"repoUrl":27,"updatedAt":672},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[860,861,862,863],{"name":663,"slug":664,"type":16},{"name":666,"slug":667,"type":16},{"name":669,"slug":670,"type":16},{"name":14,"slug":15,"type":16},{"slug":674,"name":674,"fn":675,"description":676,"org":865,"tags":866,"stars":26,"repoUrl":27,"updatedAt":691},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[867,868,869,870],{"name":680,"slug":681,"type":16},{"name":683,"slug":684,"type":16},{"name":686,"slug":687,"type":16},{"name":689,"slug":690,"type":16}]