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troubleshooting-flows

Classify Celigo job outcomes and analyze error patterns to isolate failing steps.

3|2|Updated May 20, 2026
Search Tags:#data pipeline#error diagnosis#execution logs#celigo#flow debugging#HTTP request analysis#test-run trace
One-click install
npx skills add https://github.com/celigo/ai --skill troubleshooting-flows
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: troubleshooting-flows
Source: https://github.com/celigo/ai/tree/main/skills/troubleshooting-flows
Command: npx skills add https://github.com/celigo/ai --skill troubleshooting-flows

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Troubleshooting-flows helps you diagnose why a Celigo flow fails, partially fails, returns no records, or runs slowly so you can restore correct processing quickly and systematically.

Core Features & Use Cases

  • Flow health triage by job status: distinguish total failure, partial failure, empty runs, stuck jobs, and intermittent behavior using job metrics like success/error counts and page generation/processing.
  • Error pattern diagnosis: group errors by message pattern to identify root causes instead of manually reading thousands of messages.
  • Record-level and HTTP-level inspection: inspect execution logs, per-step errors, and raw request/response details to confirm configuration issues vs data-dependent issues.
  • Safe iteration and production-grade tracing: use test runs for fast, low-risk verification, then use end-to-end tracing for silent logic bugs or production incidents.
  • Fix and recovery workflow: retry failed records, resolve expected errors, update retry data for specific failing records, and verify the fix with clean re-runs.

Quick Start

Ask the AI to help you diagnose a failing flow by first checking the most recent job status and identifying which step has the highest error count, then analyze error patterns and inspect the raw request/response for the failing step.

Frequently Asked Questions about troubleshooting-flows

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I troubleshoot a Celigo flow that failed with no records processed?▼

To troubleshoot a Celigo flow with zero records processed, check the job status to classify it as an empty run, then inspect page generation metrics and execution logs to determine if the source query returned no data or failed before processing.

What is the best way to diagnose partial failures in a Celigo integration flow?▼

Diagnosing partial failures in a Celigo flow requires grouping error messages by pattern to identify root causes, then isolating the specific step with the highest error count for record-level and HTTP-level request inspection.

Why does my Celigo scheduled flow fail intermittently and how do I trace it?▼

Intermittent Celigo flow failures are traced by running end-to-end trace workflows on production jobs to capture silent logic bugs, analyzing raw HTTP request and response details, and comparing execution logs across successful and failed runs.

How do I isolate a stuck or long-running Celigo job?▼

Isolate a stuck or long-running Celigo job by using Celigo job diagnostic commands to pull error summaries and execution logs, identifying which step is hanging, and inspecting the raw request detail to confirm if it is a timeout or configuration issue.

Can I safely retry failed records in a Celigo flow without rerunning the entire job?▼

Yes, you can safely retry failed records in a Celigo flow by first using a test run for low-risk verification, updating the retry data for specific failing records, and verifying the fix with a clean re-run instead of executing the full production job.

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