Extrae listas estructuradas de empresas desde directorios usando Firecrawl. Ideal para extraer datos de YC, Crunchbase, Product Hunt, G2, directorios de startups, directorios por categoría o bases de datos empresariales personalizadas a JSON, CSV, listas listas para CRM o tablas de investigación.
Este skill permite a un agente de IA (como Claude Code, Cursor, Codex, etc.) extraer datos de directorios de empresas de forma estructurada y masiva, utilizando Firecrawl como motor de scraping. Es especialmente útil para investigadores de mercado, reclutadores, equipos de ventas o desarrolladores que necesiten recopilar información de cientos o miles de empresas desde plataformas como Y Combinator, Crunchbase, Product Hunt, G2, directorios de startups, directorios por categoría o cualquier base de datos empresarial pública. El skill se encarga de navegar por listados paginados, extraer campos como nombre, descripción, sitio web, ubicación, tecnología usada, redes sociales y más, y luego devolver los datos en formatos listos para usar: JSON, CSV, listas compatibles con CRM (CSV enriquecido) o tablas Markdown para investigación. Al estar basado en Firecrawl, es compatible con cualquier stack de desarrollo que pueda ejecutar JavaScript y llamadas a APIs, y está diseñado para ser invocado mediante comandos de terminal o scripts de automatización. La principal ventaja es que elimina la necesidad de escribir y mantener scrapers complejos, permitiendo a los usuarios obtener datos limpios y estructurados con una sola instrucción.
npx skills add https://github.com/firecrawl/firecrawl-workflows/tree/main/skills/firecrawl-company-directoriesInstalled? Explore more Investigación y análisis de datos skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
Extrae listas estructuradas de empresas desde directorios con Firecrawl. Úsalo para extraer datos de YC, Crunchbase, Product Hunt, G2, directorios de startups, directorios por categoría o bases de datos empresariales personalizadas a JSON, CSV, listas listas para CRM o tablas de investigación.
This repo contains 15 individual skills — each has its own dedicated page.
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.
Build a knowledge base from web content with Firecrawl. Use for local reference docs, RAG-ready chunks, fine-tuning datasets, documentation mirrors, topic corpora, or LLM-ready markdown organized from web sources.
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.
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Agent skill repository discovered by 10x-chat research.
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.