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Firecrawl Workflows

Organization
firecrawl
firecrawl-workflows

Run outcome-focused Firecrawl workflows that produce deliverables such as research reports, literature reviews over published papers, 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.

Overview

Publisherfirecrawl
Repositoryfirecrawl-workflows
Skill namefirecrawl-workflows
Stars
175
Forks
38
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Firecrawl Workflows 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-workflows
  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-workflows .claude/skills/firecrawl-workflows
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Firecrawl Workflows 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 Workflows 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 Workflows 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 Workflows

Use this when the user wants a finished deliverable powered by Firecrawl, not only raw web extraction and not product-code integration.

Choose The Workflow

If no existing workflow fits, use this generic process and produce a reusable pattern that could become a new skill.

Required Intake

Infer the workflow, inputs, audience, and output format from the user's request and surrounding context. If enough is clear, start immediately.

Ask at most 1-3 concise clarifying questions only when a missing input would block the work, such as:

  • the URL, company, topic, or source to analyze
  • the desired deliverable or output format
  • a constraint that would materially change the workflow

Use the host agent's normal way to ask clarifying questions. Do not depend on a harness-specific function name.

Default Process

  1. Confirm the workflow and final artifact.
  2. Collect web evidence with Firecrawl through the CLI or equivalent Firecrawl tool surface.
  3. Save or cite source evidence so the final claims are traceable.
  4. Run independent research units in parallel when available.
  5. Synthesize findings into the requested deliverable.
  6. Include a short "rerun inputs" block when the workflow could be automated.

Parallel Work

If appropriate, use sub-agents or equivalent parallel task runners for independent units such as:

  • one competitor per researcher
  • one URL or page per researcher
  • one source category per researcher
  • one analysis dimension per reviewer

Keep the handoff generic: provide the unit of work, source URLs or search terms, expected extracted fields, and output format.

Deliverable Standards

Every workflow should return:

  • a concise executive summary
  • the evidence base used
  • the analysis or artifact requested by the user
  • recommendations or next actions when useful
  • automation inputs for reruns

For authoring new workflow skills, see workflow-authoring.md.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Firecrawl Workflows AI skill do?

Run outcome-focused Firecrawl workflows that produce deliverables such as research reports, literature reviews over published papers, 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.

Why use Firecrawl Workflows on TypingMind?

Because you install it once and use it with any model. Firecrawl Workflows 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 Workflows in TypingMind?

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

Which AI models can use Firecrawl Workflows?

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 Workflows?

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

Is the Firecrawl Workflows 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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