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tavily-ai/tavily-dynamic-search

Recherche web programmatique avec isolation de contexte.

Qu'est-ce que tavily-dynamic-search ?

Ce skill permet d'effectuer des recherches web automatisées tout en isolant proprement le contexte. Au lieu de charger l'intégralité du HTML brut et du code superflu d'une page dans votre fenêtre de contexte (ce qui gaspille des tokens et complique l'analyse), il utilise l'API Tavily pour obtenir des résultats filtrés, résumés et ciblés. Il est conçu pour les agents comme Claude Code, Cursor ou Codex, qui ont besoin d'informations fraîches sur le web sans se noyer dans le bruit. Le skill se déclenche automatiquement sur des requêtes comme "recherche", "trouve", "quelles sont les dernières nouvelles sur", ou toute demande de "filtre les résultats" ou "extrais les points clés". Il est idéal pour la veille technologique, la recherche de correctifs, l'analyse de concurrents, ou toute tâche de collecte d'information où seuls les détails pertinents doivent être conservés. Enfin, il prend en charge plusieurs plateformes d'agents (Claude Code, Cursor, Codex via OpenHands) et offre des options avancées comme la recherche de pages web spécifiques, l'extraction de contenu structuré, et la configuration du nombre de résultats.

Compatible avec~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/tavily-ai/skills/tree/main/skills/tavily-dynamic-search

Installed? Explore more Recherche et analyse de données skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →

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Documentation

Que fait tavily-dynamic-search ?

Recherche web programmatique avec isolation de contexte. Utilisez ce skill pour toute tâche de recherche où vous devez chercher sur le web, filtrer les résultats et extraire des informations spécifiques — sans polluer votre fenêtre de contexte avec du HTML brut et du contenu superflu. C'est le skill par défaut pour la recherche web. Déclenché par "recherche", "trouve", "quelles sont les dernières nouvelles sur", ou toute requête nécessitant des informations web actuelles. À utiliser également lorsqu'on vous demande de "rechercher et filtrer", "trouver les parties importantes" ou "extraire les détails clés" — tout cas où l'utilisateur souhaite un contenu organisé et sans bruit.

Individual skills in this repo

This repo contains 11 individual skills — each has its own dedicated page.

tavily-ai/crawl

Crawl any website and save pages as local markdown files. Use when you need to download documentation, knowledge bases, or web content for offline access or analysis. No code required - just provide a URL.

tavily-ai/extract

Extract content from specific URLs using Tavily's extraction API. Returns clean markdown/text from web pages. Use when you have specific URLs and need their content without writing code.

tavily-ai/research

Comprehensive research grounded in web data with explicit citations. Use when you need multi-source synthesis—comparisons, current events, market analysis, detailed reports.

tavily-ai/search

Search the web using Tavily's LLM-optimized search API. Returns relevant results with content snippets, scores, and metadata. Use when you need to find web content on any topic without writing code.

tavily-ai/tavily-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.

tavily-ai/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://", "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.

tavily-ai/tavily-crawl

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 /docs", "bulk extract", or needs content from many pages on the same domain. Supports depth/breadth control, path filtering, semantic instructions, and saving each page as a local markdown file.

tavily-ai/tavily-extract

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.

tavily-ai/tavily-map

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.

tavily-ai/tavily-research

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.

tavily-ai/tavily-search

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.

Skills associés

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

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affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

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affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

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The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.

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langgenius/backend-code-review

Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.

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