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Firecrawl Knowledge Base

This workflow turns websites or topics into organized markdown that LLMs can actually work with. Point it at documentation sites, API references, or even just a topic, and it'll use Firecrawl's map and scrape tools to pull everything down into a structured knowledge base. The onboarding is refreshingly sparse,it infers what you want and only asks clarifying questions if truly blocked. You get different output modes depending on whether you're building RAG chunks, fine-tuning datasets, or just mirroring docs locally. The parallel execution for large sites and the opinionated file structure make it feel production-ready rather than proof-of-concept. Good fit if you're tired of manually organizing web content for AI context.

skills.sh installs
32.9K
GitHub stars
221
last updated
Aug 21, 2026

Install

$ npx -y skills add firecrawl/firecrawl-workflows --skill firecrawl-knowledge-base --agent claude-code

Installs into .claude/skills of the current project.

Files

Firecrawl Knowledge Base

Use this to turn URLs or topics into organized LLM-ready content.

Onboarding Interview

Infer the source, goal, depth, and output location from context. If the source and goal are clear, proceed immediately.

Ask at most 1-3 concise questions only if blocked, such as the source URL/topic, whether the output is reference/RAG/training/docs, or training format if training is requested.

Firecrawl Collection Plan

Use Firecrawl map for documentation sites, search for topic-based corpora, scrape pages into markdown, and preserve code examples and tables.

For files, follow the Firecrawl download-style convention:

.firecrawl/
  <hostname>/
    <path>/
      index.md

Parallel Work

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

  • one docs section per researcher
  • official docs, tutorials, community discussions, and references by source type
  • source scraping vs chunk generation vs manifest generation

Output Modes

Sponsors

Details

Repository
github.com/firecrawl/firecrawl-workflows
Categories
DevOps & CI/CD, Documentation, AI & Agent Building
First seen
Jun 3, 2026

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