Construisez une base de connaissances à partir de contenu web avec Firecrawl. Utilisez-la pour des docs de référence locales, des chunks prêts pour le RAG, des ensembles de données de fine-tuning, des miroirs de documentation, des corpus thématiques ou du Markdown prêt pour LLM organisé à partir de sources web.
Cette compétence vous permet de construire une base de connaissances structurée à partir de contenu web en utilisant Firecrawl. Elle est idéale pour les développeurs et les utilisateurs d'agents IA qui souhaitent extraire, organiser et convertir des pages web en Markdown prêt pour les modèles de langage (LLM), que ce soit pour des documents de référence locaux, des chunks optimisés pour le RAG (Retrieval-Augmented Generation), des ensembles de données pour le fine-tuning, des miroirs de documentation, des corpus thématiques ou tout autre besoin de connaissances structurées. La compétence supporte les agents comme Claude Code, Cursor et Codex, et fonctionne en automatisant le crawling, le scraping et la conversion du contenu web en Markdown propre et sémantique. Grâce à son SKILL.md détaillé, elle explique comment configurer l'URL source, les options de crawl (profondeur, limites, filtres), et le format de sortie (Markdown, JSON, HTML). Elle est particulièrement utile pour les projets d'ingénierie logicielle nécessitant une documentation locale riche ou des datasets pour l'entraînement de modèles.
npx skills add https://github.com/firecrawl/firecrawl-workflows/tree/main/skills/firecrawl-knowledge-baseInstalled? Explore more Rédaction et édition skills: steipete/notion, langchain-ai/langchain, bytedance/podcast-generation · View all 6 →
Construisez une base de connaissances à partir de contenu web avec Firecrawl. Utilisez-la pour des docs de référence locales, des chunks prêts pour le RAG, des ensembles de données de fine-tuning, des miroirs de documentation, des corpus thématiques ou du Markdown prêt pour LLM organisé à partir de sources web.
This repo contains 15 individual skills — each has its own dedicated page.
Extract structured company lists from directories with Firecrawl. Use for scraping YC, Crunchbase, Product Hunt, G2, startup directories, category directories, or custom company databases into JSON, CSV, CRM-ready lists, or research tables.
Monitor competitor pricing, features, changelogs, dashboards, and product changes with Firecrawl. Use for recurring competitive intelligence, pricing tier extraction, feature change tracking, or structured competitor alerts.
Pull metrics from analytics dashboards and internal web tools with Firecrawl browser. Use when the user needs dashboard reporting, cross-platform metric summaries, authenticated analytics extraction, date-range reports, or structured metrics from web dashboards.
Run multi-source deep research with Firecrawl. Use when the user asks to research a topic, compare perspectives, produce a sourced briefing, investigate a technical or market question, or synthesize web evidence across many sources.
Walk through a product's key flows with Firecrawl browser and produce a structured UX/product walkthrough. Use for signup, onboarding, pricing, docs, dashboard, product demo prep, UX teardown, and first-run experience analysis.
Ingest public or authenticated knowledge bases and docs portals with Firecrawl browser. Use for JS-heavy docs, login-gated portals, paginated help centers, support knowledge bases, or structured JSON/markdown extraction from documentation sites.
Generate structured lead lists from prospect databases and web directories with Firecrawl browser. Use for finding prospects by role, company type, industry, stage, location, technologies, or other criteria and exporting CRM-ready JSON or CSV.
Produce pre-meeting lead intelligence briefs with Firecrawl. Use when the user needs company research, person research, recent news, talking points, pain points, or outreach preparation before a sales call, partnership meeting, investor conversation, or customer interview.
Extract market, financial, earnings, industry, and company metrics with Firecrawl. Use when the user asks for market research, industry trends, public company data, financial comparisons, earnings research, or structured market reports.
QA test a live website with Firecrawl browser and scrape evidence. Use when the user wants exploratory QA, form testing, navigation/link checks, responsive checks, performance observations, bug reports, or a pre-launch quality review.
Find and synthesize research papers, whitepapers, PDFs, technical reports, and academic sources with Firecrawl. Use when the user wants a literature review, paper summary, research landscape, or sourced synthesis from PDFs and scholarly/industry publications.
Audit a website's SEO with Firecrawl. Use when the user asks for an SEO audit, metadata and heading review, sitemap/site-structure analysis, keyword opportunities, competitor SERP comparison, or prioritized search optimization recommendations.
Research products across the web with Firecrawl and produce a shopping recommendation or cart-ready summary. Use when the user wants to compare products, find the best option, evaluate reviews, respect budget/preferences, or shop with a saved browser session.
Extract any website's design system into an agent-ready DESIGN.md using Firecrawl scrape evidence. Use when the user wants colors, fonts, spacing, components, layout patterns, or brand/UI guidance from a website so AI agents can create new websites, clone a look, or build pages inspired by that design.
Run outcome-focused Firecrawl workflows that produce deliverables such as research reports, SEO audits, QA reports, lead lists, knowledge bases, website design systems, and other structured web-data artifacts. Use when the user wants Firecrawl to complete a business, marketing, product, or creative workflow rather than merely scrape a page or integrate API calls into code.
Notion CLI/API for pages, Markdown content, data sources, files, comments, search, Workers, and raw API calls.
The agent engineering platform.
Use this skill when the user requests to generate, create, or produce podcasts from text content. Converts written content into a two-host conversational podcast audio format with natural dialogue.
Analyze and optimize tweets for maximum reach using Twitter's open-source algorithm insights. Rewrite and edit user tweets to improve engagement and visibility based on how the recommendation system ranks content.
Extracts and analyzes competitors' ads from ad libraries (Facebook, LinkedIn, etc.) to understand what messaging, problems, and creative approaches are working. Helps inspire and improve your own ad campaigns.
Context7 Platform -- Up-to-date code documentation for LLMs and AI code editors