Agent skill
monitoring
Observability patterns for production - logging, error tracking, analytics. Use when setting up monitoring.
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/monitoring-djnsty23-claude-auto-dev
SKILL.md
Monitoring Skill
Quick Commands
| Say | Action |
|---|---|
add logging |
Set up structured logging |
add error tracking |
Integrate Sentry/error boundary |
add analytics |
Add Vercel Analytics |
Structured Logging
// lib/logger.ts
type LogLevel = 'debug' | 'info' | 'warn' | 'error';
interface LogContext {
userId?: string;
action?: string;
[key: string]: unknown;
}
export function log(level: LogLevel, message: string, context?: LogContext) {
const entry = {
timestamp: new Date().toISOString(),
level,
message,
...context
};
if (process.env.NODE_ENV === 'production') {
console[level](JSON.stringify(entry));
} else {
console[level](message, context);
}
}
Error Boundary
// components/error-boundary.tsx
'use client';
import { Component, ReactNode } from 'react';
interface Props {
children: ReactNode;
fallback?: ReactNode;
}
interface State {
hasError: boolean;
error?: Error;
}
export class ErrorBoundary extends Component<Props, State> {
state: State = { hasError: false };
static getDerivedStateFromError(error: Error): State {
return { hasError: true, error };
}
componentDidCatch(error: Error, errorInfo: React.ErrorInfo) {
// Log to external service
log('error', 'React error boundary caught error', {
error: error.message,
stack: error.stack,
componentStack: errorInfo.componentStack
});
}
render() {
if (this.state.hasError) {
return this.props.fallback ?? <div>Something went wrong</div>;
}
return this.props.children;
}
}
Vercel Analytics
// app/layout.tsx
import { Analytics } from '@vercel/analytics/react';
import { SpeedInsights } from '@vercel/speed-insights/next';
export default function RootLayout({ children }) {
return (
<html>
<body>
{children}
<Analytics />
<SpeedInsights />
</body>
</html>
);
}
API Route Monitoring
// lib/api-monitor.ts
export function withMonitoring<T>(
handler: () => Promise<T>,
context: { route: string; method: string }
): Promise<T> {
const start = Date.now();
return handler()
.then(result => {
log('info', 'API request completed', {
...context,
duration: Date.now() - start,
status: 'success'
});
return result;
})
.catch(error => {
log('error', 'API request failed', {
...context,
duration: Date.now() - start,
error: error.message
});
throw error;
});
}
Health Check Endpoint
// app/api/health/route.ts
import { NextResponse } from 'next/server';
export async function GET() {
const health = {
status: 'ok',
timestamp: new Date().toISOString(),
uptime: process.uptime(),
version: process.env.VERCEL_GIT_COMMIT_SHA?.slice(0, 7) ?? 'dev'
};
return NextResponse.json(health);
}
Key Metrics to Track
| Metric | Why |
|---|---|
| Response time (p50, p95, p99) | User experience |
| Error rate | Reliability |
| Request count | Traffic patterns |
| Memory usage | Resource leaks |
| Cold start duration | Serverless performance |
Best Practices
DO:
- Use structured JSON logs in production
- Include request IDs for tracing
- Set up alerting thresholds
- Monitor Core Web Vitals
- Track user-facing errors separately
DON'T:
- Log sensitive data (passwords, tokens)
- Log every request in detail (costs)
- Ignore client-side errors
- Skip error context
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