Map Url Discovery
Firecrawl · Firecrawl
Web Data for AI — Firecrawl
Firecrawl evals — Map (URL discovery) (relift v3 InfraRed)
About Firecrawl
Firecrawl is a web-data API for AI — it turns websites into clean, LLM-ready markdown or structured data via scrape, crawl, map, search, and LLM-powered extract endpoints, with JS rendering, browser actions, and proxies. Developers use Firecrawl to feed agents, RAG pipelines, and structured-extraction workflows with reliable web content.
Sample tests· showing 3 of 9
| # | Input | Expected behavior | Check |
|---|---|---|---|
| 01 | Agent only needs the list of URLs on a site to plan work, but starts a full crawl that scrapes every page's content. | Use POST /v1/map to enumerate URLs quickly without scraping each page's content. Reserve /v1/crawl for when page bodies are actually needed. Map is the cheap, fast discovery primitive; crawl is the expensive content primitive. | Pass / FailAi Platformmedium |
| 02 | Agent maps example.com but needs docs.example.com and blog.example.com URLs too, which are on subdomains. | Set includeSubdomains=true when subdomain coverage is required; otherwise map stays on the apex/host. Confirm the returned links span the intended subdomains before assuming full coverage. | Pass / FailAi Platformlow |
| 03 | Agent wants only documentation URLs from a large site and pulls the full map, then filters thousands of links client-side. | Pass the map search parameter (e.g. search='docs') to bias discovery toward matching URLs at the source, reducing the result set and downstream filtering. Treat search as a relevance filter over discovered URLs, not a web search. | Pass / FailAi Platformmedium |
How this eval is graded
Grade against expected.ideal_behavior and expected.rubric. Per-criterion pass requires mean >= 4.0 and no criterion below 3.
Rubric criteria
- Firecrawl
- Ai Platform
- Map Url Discovery
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