mcpbeat

Firecrawl Deep Research

firecrawl/firecrawl-deep-research

| findings, contrarian views, open questions, and full sources. Use only when the user needs rigorous synthesis of a complex topic (scientific, technical, policy, or market-analytical) that cannot be answered with a short search, and wants a formal written report, not a recommendation list. Do not use for product picks, top-N lists, quick lookups, or routine "find out about X" tasks. If the request does not clearly need this kind of report, do not use this skill.

868 tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
110
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/firecrawl/firecrawl-workflows --skill firecrawl-deep-research

The instruction itself

6 sections, as written by the author

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.

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.

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.

How to use it

Copy the folder

Take firecrawl/firecrawl-deep-research from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.