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Error Tracking

  • 412 installs
  • 305 repo stars
  • Updated March 4, 2026
  • aj-geddes/useful-ai-prompts

error-tracking is an agent skill that implements Sentry exception monitoring with release tracking, source maps, and performance sampling for developers who need production error visibility in Node.js or Python apps.

About

error-tracking in aj-geddes/useful-ai-prompts guides Sentry integration for automatic exception capture, release tracking, and performance issue detection in production applications. The skill includes a quick start with @sentry/cli, @sentry/node, and sentry init, plus six reference guides: Sentry setup, Express middleware integration, Python integration, source maps and release management, custom error context, and performance monitoring. Best practices cover sample rate tuning, breadcrumb usage, user context, sensitive data filtering, and CI/CD release creation while warning against 100% error sampling and PII in context. Reference markdown files in references/ provide stack-specific implementation steps agents can follow sequentially during production rollout. Developers reach for error-tracking when launching services without observability, debugging production stability, or correlating exceptions with deploy versions. Triggers include Sentry setup, production bug tracking, and application stability analysis for Node.js and Python backends.

  • SDK integration patterns
  • Release and environment tagging
  • Alerting and noise reduction
  • Source map and context enrichment
  • Incident triage workflows

Error Tracking by the numbers

  • 412 all-time installs (skills.sh)
  • Ranked #105 of 596 Debugging skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/aj-geddes/useful-ai-prompts --skill error-tracking

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Listed on Skillselion
Installs412
repo stars305
Last updatedMarch 4, 2026
Repositoryaj-geddes/useful-ai-prompts

How do you set up Sentry error tracking in production?

Integrate and tune error tracking (e.g., Sentry, Rollbar) to capture exceptions, stack traces, releases, and alerting for live applications.

Who is it for?

Backend developers shipping Node.js or Python services who need structured Sentry rollout with releases and source maps before production traffic.

Skip if: Teams standardized on a different APM stack who only need log aggregation without exception capture tooling.

When should I use this skill?

User asks to set up Sentry, error monitoring, production exception tracking, release tracking, or application stability analysis.

What you get

Sentry SDK configuration, source map uploads, release tags, custom error context, and performance monitoring dashboards.

  • Sentry SDK config
  • Source map upload pipeline
  • Release tracking setup

By the numbers

  • Includes 6 reference guides in the references/ directory
  • Quick start uses @sentry/cli, @sentry/node, and sentry init

Files

SKILL.mdMarkdownGitHub ↗

Error Tracking

Table of Contents

Overview

Set up comprehensive error tracking with Sentry to automatically capture, report, and analyze exceptions, performance issues, and application stability.

When to Use

  • Production error monitoring
  • Automatic exception capture
  • Release tracking
  • Performance issue detection
  • User impact analysis

Quick Start

Minimal working example:

npm install -g @sentry/cli
npm install @sentry/node @sentry/tracing
sentry init -d

Reference Guides

Detailed implementations in the references/ directory:

GuideContents
Sentry SetupSentry Setup, Node.js Sentry Integration
Express Middleware IntegrationExpress Middleware Integration
Python Sentry IntegrationPython Sentry Integration
Source Maps and Release ManagementSource Maps and Release Management, CI/CD Release Creation
Custom Error ContextCustom Error Context
Performance MonitoringPerformance Monitoring

Best Practices

✅ DO

  • Set up source maps for production
  • Configure appropriate sample rates
  • Track releases and deployments
  • Filter sensitive information
  • Add meaningful context to errors
  • Use breadcrumbs for debugging
  • Set user information
  • Review error patterns regularly

❌ DON'T

  • Send 100% of errors in production
  • Include passwords in context
  • Ignore configuration for environment
  • Skip source map uploads
  • Log personally identifiable information
  • Use without proper filtering
  • Disable tracking in production

Related skills

How it compares

Pick error-tracking for Sentry-first exception and release workflows; pick infrastructure-monitoring skills when the gap is host metrics rather than application exceptions.

FAQ

What stacks does error-tracking cover?

error-tracking includes reference guides for Node.js Sentry setup, Express middleware integration, Python Sentry integration, source maps, custom error context, and performance monitoring.

What Sentry practices does error-tracking recommend?

error-tracking advises configuring sample rates, uploading source maps, tracking releases in CI/CD, filtering sensitive data, and using breadcrumbs while avoiding 100% production error capture.

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