About error-tracking
A skill for configuring Sentry-based error tracking in applications. It covers exception capture, release management, performance monitoring, and practices for analyzing errors and user impact.
Key features
- 01Sentry setup and integration
- 02Exception and performance monitoring
- 03Source maps and release management
- 04Custom error context and filtering
- 05Error analysis best practices
Use cases
- 01Monitoring production application errors
- 02Tracking releases and deployments
- 03Finding performance issues
- 04Assessing user impact of errors
Install
Copy the command and run it in a terminal.
$
npx skills add https:/ / github.com/ aj-geddes/ useful-ai-prompts --skill error-trackingAfter installing, type/error-trackingin Claude Code to confirm it loaded.
Bundled files
References and scripts installed along with SKILL.md.
references/custom-error-context.mdexpress-middleware-integration.mdperformance-monitoring.mdpython-sentry-integration.mdsentry-setup.mdsource-maps-and-release-management.mdscripts/validate-api.shtemplates/api-scaffold.yamlDetails
From the project READMEError 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:
| Guide | Contents |
|---|---|
| Sentry Setup | Sentry Setup, Node.js Sentry Integration |
| Express Middleware Integration | Express Middleware Integration |
| Python Sentry Integration | Python Sentry Integration |
| Source Maps and Release Management | Source Maps and Release Management, CI/CD Release Creation |
| Custom Error Context | Custom Error Context |
| Performance Monitoring | Performance 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
Comments
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