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error-monitoring

Set up or review production error monitoring to capture unhandled errors, failed requests, and performance signals. Check event context, release labels, and alert routing so teams receive useful information when problems occur.

OriginalShow the original description

Use when setting up a new project's production observability stack, reviewing incident response readiness, or investigating why errors are going undetected.

Run score Not tested

See how to install

Good for

  • Setting up error monitoring for a new production app
  • Investigating errors that monitoring fails to capture
  • Reviewing critical alerts and on-call routing
  • Checking user context and release labels on error events

Overview

What it does

This skill sets up monitoring to collect errors from a production app and support investigation and alerts. For configurations using SDKs from services such as Sentry, Datadog, or Bugsnag, it checks unhandled exceptions, Promise rejections, framework errors such as those in React, and failed network requests. It also reviews attached user information, release versions, and environments, along with alert thresholds and contacts for serious errors.

When it helps

Use it when preparing production monitoring for a new project or reviewing incident response arrangements. If errors do not reach the monitoring service, it examines initialization, overly broad filters, and code that swallows errors along the way. Its scope also includes measurements from actual usage and Core Web Vitals, metrics related to the experience of using a page.

Example requests

  • “Review the monitoring SDK initialization and find gaps in collecting unhandled errors or failed network requests.”
  • “Attach release versions and environments to errors, and configure alerts so the responsible team is notified of serious failures.”

Notes

Monitoring requires an error monitoring service such as Sentry, Datadog, or Bugsnag, together with integration of its SDK.

This overview was written by AI (OpenAI Codex) from the public SKILL.md. Check the original below for the exact behavior.

Document check

AI checked the SKILL.md for operations that need care and for setup requirements. The score comes only from actually running the skill (hands-on test).

SafetyAre sending data, deleting files, and running commands disclosed?
BPartly lackingIt directs attaching user information for monitoring services but gives no transmission scope or confirmation procedure.
Easy setupDoes it need few tools or API keys, and are they documented?
BPartly lackingA monitoring service and SDK are identified as requirements, but service preparation and installation commands are not provided.

Not counted in the score. Rated by AI (OpenAI Codex) as of Oct 23, 2026. Treat it as a guide and read the original before installing.

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Files included (2)

  • SKILL.md2.2 KB
  • references/rule.md7.9 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Integrate real-time error monitoring in production

Production errors are invisible without monitoring. Users rarely file detailed bug reports — they simply leave. Error monitoring gives you actionable stack traces, breadcrumbs, and user context within seconds of an issue occurring, cutting mean time to detect (MTTD) from days to minutes and dramatically reducing the cost of incidents.

Quick Reference

  • Install an error monitoring SDK (Sentry, Datadog, Bugsnag, etc.) early in the app entry point
  • Capture unhandled exceptions, unhandled promise rejections, and React error boundaries
  • Attach user context, release version, and environment to every event
  • Configure alert thresholds and on-call routing so critical errors page the right team
  • Capture failed network requests and production RUM signals such as Core Web Vitals

Check

Check whether an error monitoring service is configured and capturing unhandled errors, promise rejections, React/framework-level errors, failed network requests, and production Core Web Vitals signals.

Fix

Integrate an error monitoring SDK, configure environment and release tagging, capture failed network requests and RUM metrics, and set up alerts for critical error thresholds and regressions.

Explain

Explain how error monitoring services work, what signals they capture, and how error grouping reduces alert noise.

Code Review

Review the monitoring initialisation code. Flag missing user context, absent release tagging, overly broad event filters, missing network instrumentation, and any patterns that would swallow errors before they reach the monitoring service.


For full implementation details, code examples, and framework-specific guidance, see references/rule.md.

Rule page: https://frontendchecklist.io/rules/testing/error-monitoring

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