Claude Code Plugins

Community-maintained marketplace

Feedback

|

Install Skill

1Download skill
2Enable skills in Claude

Open claude.ai/settings/capabilities and find the "Skills" section

3Upload to Claude

Click "Upload skill" and select the downloaded ZIP file

Note: Please verify skill by going through its instructions before using it.

SKILL.md

name coderabbit-observability
description Set up comprehensive observability for CodeRabbit integrations with metrics, traces, and alerts. Use when implementing monitoring for CodeRabbit operations, setting up dashboards, or configuring alerting for CodeRabbit integration health. Trigger with phrases like "coderabbit monitoring", "coderabbit metrics", "coderabbit observability", "monitor coderabbit", "coderabbit alerts", "coderabbit tracing".
allowed-tools Read, Write, Edit
version 1.0.0
license MIT
author Jeremy Longshore <jeremy@intentsolutions.io>

CodeRabbit Observability

Overview

Set up comprehensive observability for CodeRabbit integrations.

Prerequisites

  • Prometheus or compatible metrics backend
  • OpenTelemetry SDK installed
  • Grafana or similar dashboarding tool
  • AlertManager configured

Metrics Collection

Key Metrics

Metric Type Description
coderabbit_requests_total Counter Total API requests
coderabbit_request_duration_seconds Histogram Request latency
coderabbit_errors_total Counter Error count by type
coderabbit_rate_limit_remaining Gauge Rate limit headroom

Prometheus Metrics

import { Registry, Counter, Histogram, Gauge } from 'prom-client';

const registry = new Registry();

const requestCounter = new Counter({
  name: 'coderabbit_requests_total',
  help: 'Total CodeRabbit API requests',
  labelNames: ['method', 'status'],
  registers: [registry],
});

const requestDuration = new Histogram({
  name: 'coderabbit_request_duration_seconds',
  help: 'CodeRabbit request duration',
  labelNames: ['method'],
  buckets: [0.05, 0.1, 0.25, 0.5, 1, 2.5, 5],
  registers: [registry],
});

const errorCounter = new Counter({
  name: 'coderabbit_errors_total',
  help: 'CodeRabbit errors by type',
  labelNames: ['error_type'],
  registers: [registry],
});

Instrumented Client

async function instrumentedRequest<T>(
  method: string,
  operation: () => Promise<T>
): Promise<T> {
  const timer = requestDuration.startTimer({ method });

  try {
    const result = await operation();
    requestCounter.inc({ method, status: 'success' });
    return result;
  } catch (error: any) {
    requestCounter.inc({ method, status: 'error' });
    errorCounter.inc({ error_type: error.code || 'unknown' });
    throw error;
  } finally {
    timer();
  }
}

Distributed Tracing

OpenTelemetry Setup

import { trace, SpanStatusCode } from '@opentelemetry/api';

const tracer = trace.getTracer('coderabbit-client');

async function tracedCodeRabbitCall<T>(
  operationName: string,
  operation: () => Promise<T>
): Promise<T> {
  return tracer.startActiveSpan(`coderabbit.${operationName}`, async (span) => {
    try {
      const result = await operation();
      span.setStatus({ code: SpanStatusCode.OK });
      return result;
    } catch (error: any) {
      span.setStatus({ code: SpanStatusCode.ERROR, message: error.message });
      span.recordException(error);
      throw error;
    } finally {
      span.end();
    }
  });
}

Logging Strategy

Structured Logging

import pino from 'pino';

const logger = pino({
  name: 'coderabbit',
  level: process.env.LOG_LEVEL || 'info',
});

function logCodeRabbitOperation(
  operation: string,
  data: Record<string, any>,
  duration: number
) {
  logger.info({
    service: 'coderabbit',
    operation,
    duration_ms: duration,
    ...data,
  });
}

Alert Configuration

Prometheus AlertManager Rules

# coderabbit_alerts.yaml
groups:
  - name: coderabbit_alerts
    rules:
      - alert: CodeRabbitHighErrorRate
        expr: |
          rate(coderabbit_errors_total[5m]) /
          rate(coderabbit_requests_total[5m]) > 0.05
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "CodeRabbit error rate > 5%"

      - alert: CodeRabbitHighLatency
        expr: |
          histogram_quantile(0.95,
            rate(coderabbit_request_duration_seconds_bucket[5m])
          ) > 2
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "CodeRabbit P95 latency > 2s"

      - alert: CodeRabbitDown
        expr: up{job="coderabbit"} == 0
        for: 1m
        labels:
          severity: critical
        annotations:
          summary: "CodeRabbit integration is down"

Dashboard

Grafana Panel Queries

{
  "panels": [
    {
      "title": "CodeRabbit Request Rate",
      "targets": [{
        "expr": "rate(coderabbit_requests_total[5m])"
      }]
    },
    {
      "title": "CodeRabbit Latency P50/P95/P99",
      "targets": [{
        "expr": "histogram_quantile(0.5, rate(coderabbit_request_duration_seconds_bucket[5m]))"
      }]
    }
  ]
}

Instructions

Step 1: Set Up Metrics Collection

Implement Prometheus counters, histograms, and gauges for key operations.

Step 2: Add Distributed Tracing

Integrate OpenTelemetry for end-to-end request tracing.

Step 3: Configure Structured Logging

Set up JSON logging with consistent field names.

Step 4: Create Alert Rules

Define Prometheus alerting rules for error rates and latency.

Output

  • Metrics collection enabled
  • Distributed tracing configured
  • Structured logging implemented
  • Alert rules deployed

Error Handling

Issue Cause Solution
Missing metrics No instrumentation Wrap client calls
Trace gaps Missing propagation Check context headers
Alert storms Wrong thresholds Tune alert rules
High cardinality Too many labels Reduce label values

Examples

Quick Metrics Endpoint

app.get('/metrics', async (req, res) => {
  res.set('Content-Type', registry.contentType);
  res.send(await registry.metrics());
});

Resources

Next Steps

For incident response, see coderabbit-incident-runbook.