firecrawl-deep-research

Execute pesquisa aprofundada com múltiplas fontes usando Firecrawl. Use quando o usuário pedir para pesquisar um tópico, comparar perspectivas, produzir um briefing com fontes, investigar uma questão técnica ou de mercado, ou sintetizar evidências da web em várias fontes.

npx skills add https://github.com/firecrawl/firecrawl-workflows --skill firecrawl-deep-research

Firecrawl Deep Research

Use this only for report-scale research: a rigorous, cited synthesis the user explicitly wants delivered as a formal written report. If the request is a product pick, a top-N list, a quick lookup, or anything answerable with a short search, stop; do not use this skill, let the request be handled the standard way.

This skill gathers its evidence from the open web. If the evidence base is the published literature — a literature review, or a biomedical, clinical, or other scientific topic where the answer lives in papers — use firecrawl-research-papers instead; it queries Firecrawl's paper index rather than searching websites.

Onboarding Interview

Infer the topic and output format from context. Before starting, unless already specified, always ask one short question to define the scope:

"How long do you want this research task to run?"

Map the answer to a depth tier in the Collection Plan below:

  • A few minutes → Quick
  • ~10-15 minutes → Thorough
  • Longer / no limit → Exhaustive

If the topic itself is unclear, you may ask at most 1-2 additional concise questions (topic, or a critical angle/source constraint). Otherwise proceed once the runtime is set.

Firecrawl Collection Plan

Use Firecrawl search and scrape through the CLI or equivalent tool surface. Match depth to the runtime the user chose during onboarding.

  • Quick (~a few minutes): search 3-5 queries and scrape 5-10 high-quality sources.
  • Thorough (~10-15 minutes): search 5-10 queries from different angles and scrape 15-25 sources.
  • Exhaustive (longer): search 10+ queries and scrape 25+ sources, including primary sources, research papers, expert views, and contrarian sources.

Avoid re-scraping URLs already returned with full content from a search-with-scrape result.

When Published Papers Are The Evidence

Search and scrape reach web pages. They do not query Firecrawl's research paper index, which holds paper abstracts with full text reachable per paper — largely biomedical and life-science literature from PubMed, bioRxiv, and medRxiv, plus arXiv preprints in CS, physics, and math.

Hand off to firecrawl-research-papers when the report's evidence base is the published literature — a biomedical, clinical, drug, gene, disease, epidemiology, or public-health topic, or any request phrased as a literature review, systematic review, or survey of studies. That skill uses firecrawl_research_* (MCP) / firecrawl research (CLI) to search abstracts, expand to related papers, and verify claims inside a paper body — none of which plain search and scrape can do.

If the report needs both — the literature and market, policy, or news context — run the paper work through that skill and keep the web collection above for the rest, then synthesize here.

Note that passing categories: ["research"] to Firecrawl search does not query the paper index either. It filters an ordinary web search to research-affiliated websites — the list includes PubMed, bioRxiv, medRxiv, arXiv, and publisher sites — and returns their web pages, not the paper records behind them.

Parallel Work

If appropriate, use sub-agents or equivalent parallel task runners by research angle:

  • overview and definitions
  • technical or implementation details
  • market and industry context
  • contrarian views, risks, and limitations
  • primary sources and official docs

Each researcher should return claims, source URLs, source quality notes, and uncertainty.

Final Deliverable

Default structure:

# Deep Research: [Topic]

## Executive Summary
[2-3 paragraphs]

## Key Findings
[Numbered findings with source links]

## Detailed Analysis
[Themes, evidence, and synthesis]

## Contrarian Views And Risks
[Counterarguments, limitations, failure modes]

## Open Questions
[What remains uncertain]

## Sources
[Every URL used with a one-line note]

## Rerun Inputs
workflow: firecrawl-deep-research
topic: [topic]
depth: [quick/thorough/exhaustive]
output: [markdown/json/brief]

Quality Bar

  • Cite sources for factual claims.
  • Prefer primary sources when available.
  • Flag uncertainty and conflicting evidence.
  • Synthesize instead of listing scrape summaries.

Mais skills de firecrawl

firecrawl-research-index
firecrawl
Encontre os artigos que respondem a uma consulta de pesquisa com o Firecrawl Research, utilizando busca semântica, expansão semântica e estrutural, e verificação no corpo do texto. Use sempre esta habilidade para qualquer tarefa de localização de literatura ou recuperação de artigos — consultas de um único artigo ou conjuntos completos de múltiplos artigos.
data-analysisresearchweb-scraping
oracle
firecrawl
Melhores práticas para usar a CLI do oracle (prompt + agrupamento de arquivos, engines, sessões e padrões de anexo de arquivos).
pinecone
firecrawl
Banco de dados vetorial gerenciado para aplicações de IA em produção. Totalmente gerenciado, com escalonamento automático, busca híbrida (densa + esparsa), filtragem por metadados e namespaces.…
wpds
firecrawl
Use ao construir UIs que utilizam o WordPress Design System (WPDS) e seus componentes, tokens, padrões, etc.
audiocraft-audio-generation
firecrawl
Biblioteca PyTorch para geração de áudio, incluindo texto para música (MusicGen) e texto para som (AudioGen). Use quando precisar gerar música a partir de texto…
skypilot-multi-cloud-orchestration
firecrawl
Orquestração multi-cloud para cargas de trabalho de ML com otimização automática de custos. Use quando precisar executar treinamento ou jobs em lote em múltiplas nuvens, aproveitar…
firecrawl-seo-audit
firecrawl
Audite o SEO de um site com Firecrawl. Use quando o usuário solicitar uma auditoria de SEO, revisão de metadados e cabeçalhos, análise de sitemap/estrutura do site, oportunidades de palavras-chave, comparação de SERP de concorrentes ou recomendações priorizadas de otimização de busca.
data-analysisresearchweb-scraping
gh-issues
firecrawl
Buscar issues do GitHub, criar subagentes para implementar correções e abrir PRs, depois monitorar e tratar comentários de revisão dos PRs. Uso: /gh-issues [owner/repo] [--label…