Firecrawl Deep Research logo

Firecrawl Deep Research

Organization
firecrawl
firecrawl-deep-research

Produce an intensive, cited analytical report: executive summary, multi-angle 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. Do not use for a literature review over published papers. This skill collects evidence from the open web. A request for the literature on a biomedical, clinical, life-science, or other scientific topic — papers, studies, trials, preprints — belongs to firecrawl-research-papers, which queries Firecrawl's paper index (PubMed, bioRxiv, medRxiv, arXiv) instead of searching websites.

Overview

Publisherfirecrawl
Repositoryfirecrawl-workflows
Skill namefirecrawl-deep-research
Stars
175
Forks
38
Bundled files
Instructions only
LicenseISC
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by firecrawl on GitHub. Read the source before you install it.

Installation

Install the Firecrawl Deep Research AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/firecrawl/firecrawl-workflows/tree/main/skills/firecrawl-deep-research
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/firecrawl/firecrawl-workflows.git /tmp/firecrawl-workflows
mkdir -p .claude/skills
cp -r /tmp/firecrawl-workflows/skills/firecrawl-deep-research .claude/skills/firecrawl-deep-research
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Firecrawl Deep Research in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Firecrawl Deep Research on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Firecrawl Deep Research is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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:

markdown
# 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.

Frequently asked questions

What does the Firecrawl Deep Research AI skill do?

Produce an intensive, cited analytical report: executive summary, multi-angle 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. Do not use for a literature review over published pap...

Why use Firecrawl Deep Research on TypingMind?

Because you install it once and use it with any model. Firecrawl Deep Research is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Firecrawl Deep Research in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/firecrawl/firecrawl-workflows/tree/main/skills/firecrawl-deep-research. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Firecrawl Deep Research?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Firecrawl Deep Research?

As many as you like. As long as a model supports skills, you can use Firecrawl Deep Research with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Firecrawl Deep Research AI skill free?

Yes. It is published on GitHub by firecrawl under the ISC license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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