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Firecrawl Deep Research

When you need more than a few Google results, this skill orchestrates Firecrawl to run actual multi-source research. It searches from different angles, scrapes 5 to 25+ pages depending on depth, and synthesizes findings into a sourced report with an executive summary, key findings, contrarian views, and open questions. The template pushes for primary sources and flags uncertainty instead of pretending everything is settled. It can spin up parallel sub-agents by research angle if your task supports it. Best for technical investigations, market research, or any time you need citations and synthesis rather than raw links. Built by the Firecrawl team.

skills.sh installs
35.9K
GitHub stars
221
last updated
Aug 21, 2026

Install

$ npx -y skills add firecrawl/firecrawl-workflows --skill firecrawl-deep-research --agent claude-code

Installs into .claude/skills of the current project.

Files

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

Sponsors

Details

Repository
github.com/firecrawl/firecrawl-workflows
Category
Data Science & ML
First seen
Jun 3, 2026

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