tavily-cowork-plugin

Real-time competitive intelligence using live web data via the Tavily MCP. Use when the user wants to analyze competitors, build a battlecard, profile a competitor, monitor pricing, mine reviews, track hiring signals, map a competitive landscape, find positioning gaps, or research win/loss patterns; says "analyze competitor", "build me a battlecard", "what is X charging", "how do we compare to Y", "competitive landscape for Z", "competitor analysis", "market intelligence", or anything similar. Always uses live data — never answers competitive questions from training knowledge alone.

Find topics, keywords, and angles that competitors cover but you don't via the Tavily MCP. Use when the user wants to find content gaps, plan editorial calendars, identify SEO opportunities, see what topics competitors own, or says "what topics do competitors cover that we don't", "find content gaps", "blog topics we should write about", "where are we losing in search", "what should we write next", or anything similar. Combines site-mapping, search ranking checks, and synthesis into a prioritized opportunity list. For full SEO audits, this is the content-side companion to a technical audit.

Run a comprehensive cited research report using Tavily's deep-research agent. Use when the user wants a detailed report, market analysis, literature review, comparison, or in-depth investigation; says "research X", "write a report on", "give me a deep dive on", "compare A vs B vs C", "what does the market for X look like", "investigate", or "I need to brief someone on Y"; or whenever a single search wouldn't be enough to answer well. Returns a structured multi-source report with explicit citations. Slower than search (30–120s) — surface that to the user. For quick fact-finding, use web-search.

Extract clean markdown or text content from one or more URLs via the Tavily MCP. Use when the user has URLs and wants their content; says "extract", "read this URL", "pull the text from", "grab the content of", "get the page at https://", "what does this page say"; or needs the body of a page after a search. Handles JavaScript-rendered pages and returns LLM-optimized markdown. Up to 20 URLs per call. For finding URLs first, use web-search or site-map.

Verify claims with cited live-web sources via the Tavily MCP. Use when the user asks "is this true", "verify this", "fact-check", "find sources for", "is there evidence for", "did X actually say Y", "what are the sources on", or wants to validate something they read or wrote before publishing. Returns a verdict (supported / refuted / mixed / unverifiable) backed by primary sources where possible. For prose research without verification framing, use deep-research.

Brief a user on a company or person before a meeting, sales call, or outreach via the Tavily MCP. Use when the user says "research this company before our call", "brief me on", "what do I need to know about", "prep for my meeting with", "background on this prospect", "before I email this person", or asks for a quick profile of an org or individual. Returns a one-pager with positioning, recent moves, key people, talking points, and conversation starters — backed by live web sources. For deep market research, use deep-research instead.

Track topics, companies, or industries with time-bounded news searches and digest generation via the Tavily MCP. Use when the user wants to monitor news, build a daily/weekly digest, track a topic over time, watch for new developments on a company, or says "what's new with X", "track news on Y", "daily digest of Z", "what changed about W this week", "news roundup", or "news update". Pairs naturally with scheduled tasks for recurring digests. For one-off deep dives, use deep-research instead.

Bulk-extract clean content from many pages on a site via the Tavily MCP. Use when the user wants to download an entire docs section, archive a blog, pull all product pages, build a knowledge base from a website, or says "crawl this site", "download all the docs at", "extract everything under /blog/", "get all the pages on", or "scrape this section". Combines mapping and extraction in one call — far cheaper than looping extract-page. For URL discovery without content, use site-map. For a single URL, use extract-page.

Discover all URLs on a website without downloading content via the Tavily MCP. Use when the user wants to find a specific page on a large site, list all pages, see a site's structure, or says "map this site", "what pages exist on", "find the page about X on this site", "list all URLs", or "find the URL for". Faster than crawling — returns URLs only. Pair with extract-page once the right URL is identified. For bulk content extraction, use site-crawl.

Build a curated reading list, source bibliography, or recommended-resources digest on a topic via the Tavily MCP. Use when the user wants to learn about a topic from scratch, build a reference collection, share a reading list with their team, or says "build me a reading list on", "what should I read about", "curate sources on", "recommended resources for", "syllabus for", or "starter pack on". Returns a categorized list of high-quality sources (foundational, recent, contrarian) with one-line annotations. For one-shot synthesis, use deep-research instead.

Entry point and routing guide for the Tavily web research toolkit. Loads when the user mentions Tavily, asks how to research the web, asks "what can Tavily do", or starts a research task without specifying which Tavily skill. Explains the five Tavily MCP tools, the workflow skills built on top of them, and routes to the right narrower skill for the user's task. Use this skill first when the right Tavily entry point is unclear.

Search the live web with LLM-optimized results via the Tavily MCP. Use when the user wants to search for, find, look up, or discover sources on a topic; says "search for", "find me", "what's the latest on", "find articles about", "Google this for me"; or needs current information beyond training-data cutoff. Returns ranked results with snippets, scores, and metadata. Supports domain filtering, time ranges, and depth tuning. For deep multi-source synthesis, use deep-research instead. For pulling content from a known URL, use extract-page.