
Firecrawl Knowledge Ingest
- 29.5k installs
- 101 repo stars
- Updated June 19, 2026
- firecrawl/firecrawl-workflows
Firecrawl Knowledge Ingest is a workflow skill that ingests auth-gated and JavaScript-heavy documentation portals for RAG and knowledge systems.
About
Firecrawl Knowledge Ingest is a workflow skill that ingests auth-gated or JavaScript-heavy documentation portals. Developers use it to extract and process complex docs for RAG systems or knowledge bases. It produces LLM-ready knowledge for training data and embeddings.
- Auth-gated documentation ingestion
- JavaScript-heavy portal handling
- LLM-ready knowledge extraction
Firecrawl Knowledge Ingest by the numbers
- 29,477 all-time installs (skills.sh)
- +364 installs in the week ending Jul 28, 2026 (Skillselion tracking)
- Ranked #18 of 1,901 Documentation skills by installs in the Skillselion catalog
- Security screen: MEDIUM risk (skills.sh audit)
- Data as of Jul 28, 2026 (Skillselion catalog sync)
firecrawl-knowledge-ingest capabilities & compatibility
- Capabilities
- doc ingestion · auth handling · rag preparation · embedding generation
- Use cases
- documentation · research
- Pricing
- Freemium
npx skills add https://github.com/firecrawl/firecrawl-workflows --skill firecrawl-knowledge-ingestAdd your badge
Show developers this skill is listed on Skillselion. Paste this into your README.
| Installs | 29.5k |
|---|---|
| repo stars | ★ 101 |
| Security audit | 2 / 3 scanners passed |
| Last updated | June 19, 2026 |
| Repository | firecrawl/firecrawl-workflows ↗ |
What it does
Ingest auth-gated or complex documentation portals into RAG systems and knowledge bases.
Who is it for?
Teams building RAG systems and knowledge bases from complex docs.
Skip if: Simple static documentation.
When should I use this skill?
The user needs to ingest docs portals, help centers, or support knowledge bases with browser navigation, auth, pagination, or JS rendering for RAG.
What you get
Produces LLM-ready knowledge for training data, RAG systems, and embeddings.
- RAG-ready markdown corpus
- structured JSON docs export
- paginated help center extracts
By the numbers
- Published as version 0.1.0 in firecrawl/firecrawl-workflows
- Requires FIRECRAWL_API_KEY for hosted Firecrawl browser requests
Files
Firecrawl Knowledge Ingest
Use this when a docs portal needs browser navigation, auth, pagination, or JS rendering.
Onboarding Interview
Infer the portal URL, output format, auth needs, and page limit from context. If the portal is clear, proceed immediately.
Ask at most 1-3 concise questions only if blocked, such as the portal URL, whether authentication is required, or the desired output format.
Firecrawl Collection Plan
Use Firecrawl browser to:
- open the portal and inspect navigation
- identify sections, categories, sidebar links, and article URLs
- follow sidebar navigation, next links, pagination, load-more controls, or search
- scrape article content as markdown
- extract metadata such as title, section, last updated date, author, and tags
Try Firecrawl map as a supplement for public URLs, but use browser navigation for auth-gated or JS-heavy content.
Final Deliverable
# Knowledge Ingest: [Portal]
## Summary
[Pages extracted, sections covered, limitations]
## Output
[JSON/markdown/merged file path or content]
## Sections
[Section names and article counts]
## Failed Or Restricted Pages
[Any access/loading issues]
## Sources
[URLs extracted]
## Rerun Inputs
workflow: firecrawl-knowledge-ingest
url: [portal url]
format: [json/markdown/merged]
max_pages: [number]JSON Shape
Use source, url, extractedAt, totalArticles, and sections[] with article title, url, section, content, and metadata.
Quality Bar
- Preserve code examples, tables, and formatting.
- Strip nav chrome, headers, and footers.
- Track extraction progress and page failures.
- Respect authentication boundaries.
Related skills
How it compares
Use firecrawl-knowledge-ingest for dynamic docs portals; use static site generators or OpenAPI parsers when source docs are already structured files.
FAQ
What types of portals can it handle?
Auth-gated documentation, JavaScript-heavy UIs, and complex portal structures.
What format is the output?
LLM-ready knowledge suitable for RAG systems, training data, and embedding pipelines.
Is Firecrawl Knowledge Ingest safe to install?
skills.sh reports 2 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.