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apify-common-errors

Troubleshoot common Apify Actor and API failures by matching the exact error signature to a catalog entry. Get likely causes, copyable fixes, and commands to verify recovery for authentication, rate limits, builds, proxies, payloads, and anti-bot blocks.

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Diagnose and fix common Apify Actor and API errors. Use when an Apify run fails, an API call returns 401/403/404/413/429, a proxy connection drops, an Actor build breaks, or a scrape hits an anti-bot block, and you need the cause plus a copy-paste fix. Trigger with "apify error", "fix apify", "actor failed", "apify not working", "debug apify", "apify 429".

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适用场景

  • Diagnosing a failed or timed-out Actor run
  • Understanding an Apify API status code
  • Investigating proxy or anti-bot failures
  • Verifying that a fix restored a run

包含的文件(2)

  • SKILL.md5.1 KB
  • references/error-reference.md6.2 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Apify Common Errors

Overview

Quick diagnostic reference for the most common Apify errors. Covers Actor run failures, API errors, proxy problems, anti-bot blocks, and platform-specific issues. The full per-error catalog — raw signature, cause, diagnosis, and copy-paste fix for all ten errors — lives in references/error-reference.md; this file is the lean triage path that points you there.

Prerequisites

  • An Apify API token exported as APIFY_TOKEN (Console > Settings > Integrations).
  • Access to the Apify Console for reading run and build logs.
  • curl and jq on PATH for the diagnostic commands below; apify CLI optional for build inspection.

Instructions

Work the failure from signal to fix:

  1. Capture the exact error. Grab the Status / StatusMessage from the run, or the ApifyApiError message and HTTP code from the API response. The raw string is the key you match on.
  2. Match the signature. Find the matching entry in the table below, then open references/error-reference.md at that number for the cause, diagnosis, and fix.
  3. Diagnose before changing code. For run failures, pull the log via the API or Console (see the FAILED entry). For auth/rate/payload errors, the HTTP code already tells you the class — see Error Handling.
  4. Apply the fix from the reference, re-run, and confirm with the diagnostic commands.

Error signature → reference

#ErrorSignature to match
1Actor run FAILEDStatus: FAILED / exited with code 1
2Actor run TIMED-OUTActor timed out after N seconds
3Rate limitedRate limit exceeded (429)
4UnauthorizedAuthentication required (401)
5Build failedBuild failed: npm ERR!
6Proxy connection failed502 Bad Gateway / Could not connect to proxy
7Anti-bot blockstatus 403 / Captcha detected
8Out of memoryJavaScript heap out of memory
9Dataset push too largePayload too large (413)
10Actor not foundActor '…' not found (404)

Full detail for every row: references/error-reference.md.

Output

Working through this skill yields:

  • The identified error class (matched signature + the one of ten catalog entries).
  • The root cause and a copy-paste fix (config change, code edit, or token/proxy action).
  • A verification command whose output confirms the run recovered (status SUCCEEDED, valid username, etc.).

Error Handling

HTTP CodeMeaningRetryableAction
400Bad requestNoFix input/params
401UnauthorizedNoCheck token
403ForbiddenNoCheck permissions
404Not foundNoVerify resource ID
408TimeoutYesRetry with backoff
413Payload too largeNoReduce batch size
429Rate limitedYesAuto-retried by client
500+Server errorYesAuto-retried by client

Examples

Diagnostic commands for the most common triage steps:

# Check Apify platform status
curl -s https://api.apify.com/v2/health | jq '.'

# Verify your auth (fixes 401 diagnosis)
curl -s -H "Authorization: Bearer $APIFY_TOKEN" \
  https://api.apify.com/v2/users/me | jq '.data.username'

# Check installed package versions
npm list apify-client apify crawlee 2>/dev/null

# Get last run status (find why a run FAILED / TIMED-OUT)
curl -s -H "Authorization: Bearer $APIFY_TOKEN" \
  "https://api.apify.com/v2/acts/USER~ACTOR/runs?limit=1&desc=true" | \
  jq '.data.items[0] | {status, statusMessage, startedAt, finishedAt}'

For the worked fix behind each error — e.g. reading a run log to find a stack trace, batching dataset pushes under 9MB, or switching to residential proxies to clear a 403 — see the matching entry in references/error-reference.md.

Resources

Next Steps

For comprehensive multi-error debugging across a whole Actor project — log correlation, proxy rotation strategy, and build-cache issues — see the apify-debug-bundle skill in this pack. </content>

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