Firecrawl
For FirecrawlAI Platform

Actions And Dynamic Pages

Firecrawl · Firecrawl

Web Data for AI — Firecrawl

Evaluates Firecrawl's Actions & Dynamic Pages across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Web Data for AI eval coverage.

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.

Employees

~30

Industry

Web Data / Scraping

Headquarters

San Francisco, CA

Sample tests· showing 3 of 9

#InputExpected behaviorCheck
01

Content sits behind a 'Load more' button; a plain scrape captures only the initial page state without the expanded content.

Use an actions sequence with a click action targeting the button (plus a wait) so the dynamic content loads before capture. Verify the post-action markdown includes the expanded content rather than the initial state.

Pass / FailAi Platformhigh
02

A page requires typing a query into a search box and submitting before the target results render.

Use write/input actions to populate the field and a click/press action to submit, with waits between, so the results page renders before capture. Confirm the captured content reflects the submitted query.

Pass / FailAi Platformmedium
03

A feed lazy-loads items as the user scrolls; a single scrape captures only the first viewport of items.

Add scroll actions (repeated, with waits) to trigger lazy-loading until the needed items are present, then capture. Bound the number of scrolls to avoid unbounded loops on truly infinite feeds.

Pass / FailAi Platformhigh

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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
  • Actions And Dynamic Pages

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FirecrawlFirecrawl customers

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Frequently asked questions

What does the Actions And Dynamic Pages eval for Firecrawl Firecrawl test?+

Evaluates Firecrawl's Actions & Dynamic Pages across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Web Data for AI eval coverage.

How is the Actions And Dynamic Pages eval scored?+

The judge rubric: Grade against expected.ideal_behavior and expected.rubric. Per-criterion pass requires mean >= 4.0 and no criterion below 3.

How many test cases does this eval pack include?+

The Actions And Dynamic Pages pack for Firecrawl Firecrawl contains 9 test cases. 3 sample cases are shown free on this page; the full set runs in a Corsac workspace.

How do I run this eval?+

Sign up for Corsac, connect your model or agent endpoint, and run the Actions And Dynamic Pages pack as-is or after customizing thresholds. Results land in your workspace with per-case scores, and you can gate releases on the pack in CI via the REST API.

Run this eval in your workspace

Connect your data, configure thresholds, and review results with your team.