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Debug Firecrawl with Ask

Debug a failed job or any Firecrawl integration issue with an agentic support API
5 min read

Firecrawl /support/ask is an AI support agent exposed as an API. Describe your issue and get back a verified diagnosis with actionable fix parameters — typically in 15–30 seconds.

Think of /support/ask as a senior Firecrawl engineer on-call for your agent.

Info

The Ask API is designed primarily for AI agent callers. If you're building agents that use Firecrawl for scraping, crawling, or data extraction, wire /support/ask into your error-handling flow for autonomous issue resolution.

Two endpoints#

EndpointAuthWho it's forWhat it does
POST /support/askYour Firecrawl API keyYour agents and appsFull diagnostic loop scoped to your team
POST /support/docs-searchYour Firecrawl API keyYour agents and appsDocs-grounded answers from Firecrawl's public documentation

Quick start#

Debug a failing crawl#

Search the docs#

Debug a failed job#

Every Firecrawl job — scrape, crawl, batch scrape, search, map, or extract — can be debugged with /support/ask. Describe the failure in plain language and include the job ID when you have one; the agent pulls that job's logs and your account state before answering.

Include as much of this as you have — each piece narrows the diagnosis:

DetailWhy it helps
Job IDLets the agent read that job's logs, status, and per-page results directly
Target URLSurfaces site-specific blockers like bot protection, JS rendering, or robots rules
Error message or status codeSeparates rate limits and credit exhaustion from scrape-level failures
What you expectedDistinguishes a hard failure from a job that "succeeded" with missing content
rationaleTells the agent what the end user is after so it prioritizes the right evidence

What Ask checks for common failures#

SymptomWhat the agent investigates
Job status failedJob logs, upstream HTTP status, proxy and retry history
Crawl returned fewer pages than expectedlimit, maxDiscoveryDepth, includePaths/excludePaths, sitemap coverage, robots rules
Empty or truncated markdownClient-side rendering, waitFor timing, required actions, onlyMainContent trimming
401 / 402 / 429 responsesAPI key validity and restrictions, remaining credits, plan rate limits
Job stuck or timing outQueue state, page-level timeouts, job concurrency for your plan
Webhook never firedDelivery attempts, endpoint responses, signature verification failures

Don't have a job ID? Hover a row's URL in Activity Logs and click Copy ID, or use the id returned when you started the job.

Debug from Activity Logs#

If you'd rather not write the call yourself, the dashboard runs the same agent for you. Open Activity Logs and look for the sparkles button in the Actions column of a failed row — its tooltip reads Debug issue. It only shows up on jobs that failed or finished with errors on child requests, so successful and in-progress jobs won't have one.

Clicking it starts the diagnosis straight away; there's no prompt to write. Firecrawl sends that job's URL, endpoint, status, error message, and scrape parameters to the same agent behind /support/ask, which then reads the job's logs and your account state. Scraped page content is never included.

The panel that opens gives you:

ElementWhat it is
DiagnosisThe agent's explanation of what went wrong and what to change
Confidence badgeHigh, medium, or low — how sure the agent is in the answer
Validated badgeShown when the agent tested its own suggested fix and the test passed
Suggested fixThe corrected parameters as JSON, with a copy button — paste them into your next call
SourcesLinks to the docs pages the answer draws on

If the diagnosis doesn't resolve it, Open support ticket at the bottom of the panel files a ticket with the agent's analysis already attached, so you don't have to re-explain the failure.

Info

Dashboard debugging is capped at 30 runs per hour per team, and your team needs at least one API key — the agent runs under your own key, so it only ever sees your jobs.

Once you have a diagnosis, apply the returned fixParameters and retry — see the agent retry pattern below.

How it works#

When you call /support/ask, the AI agent:

  1. Gathers evidence — inspects your job logs, account state, credit usage, and relevant documentation in parallel
  2. Diagnoses the issue — reasons across all evidence to identify the root cause
  3. Proposes a fix — generates machine-actionable fixParameters you can apply directly to your next API call
  4. Validates the fix — when possible, tests the fix against the live Firecrawl API (e.g., retrying a scrape with adjusted parameters) and reports the result

Using Ask in your agent#

The key design pattern: call /support/ask when your Firecrawl API call fails or returns unexpected results, then use the fixParameters to retry.

Python example#

Node.js example#

Agent retry pattern#

Parameters#

/support/ask#

ParameterTypeRequiredDescription
questionstringYesWhat to debug (1–8,000 characters)
rationalestringNoRecommended for AI callers. What the end user is trying to accomplish. Helps prioritize evidence gathering.
contextobjectNoFree-form metadata from your agent, included in the debugging prompt
ParameterTypeRequiredDescription
questionstringYesThe question to answer (1–8,000 characters)

Response#

/support/ask response#

The actual answer, fixParameters, and validation.evidence are produced per request by the agent based on your specific run; the example above shows the response shape, not a real diagnosis.

/support/docs-search response#

Performance#

MetricTypicalMaximum
Latency15–30 seconds60 seconds (hard ceiling)

API Reference#

Have feedback or need help? Email help@firecrawl.com.

Are you an AI agent that needs a Firecrawl API key? See firecrawl.dev/agent-onboarding/SKILL.md for automated onboarding instructions.