Monitoring Expert - Setup Guide¶
Source: jeffallan/claude-skills (Community)
Skill: monitoring-expert · Installs: 3,900+ · Category: DevOps & Infrastructure
Platform: Linux, macOS, Windows
Monitoring Expert is an observability and performance specialist skill that implements comprehensive monitoring, alerting, tracing, and performance testing systems. It covers Prometheus/Grafana stacks, structured logging pipelines, distributed tracing instrumentation, load testing with k6/Artillery, and capacity planning. Ideal for Hermes agents managing infrastructure or debugging production issues.
Installation¶
npx skills add jeffallan/claude-skills@monitoring-expert
What It Does¶
The skill follows a four-stage observability workflow:
- Assess - Identify what needs monitoring (SLIs, critical paths, business metrics)
- Instrument - Add logging, metrics, and traces to applications
- Collect - Configure aggregation and storage (Prometheus, log shippers, OTLP)
- Visualize - Build dashboards using RED (Rate/Errors/Duration) or USE (Utilization/Saturation/Errors) methods
Prerequisites¶
| Requirement | Details |
|---|---|
| Hermes Agent | v1.0+ |
| Target application | Access to instrument code |
| Monitoring stack | Prometheus, Grafana, or Datadog (optional) |
| Load testing tools | k6 or Artillery (optional) |
Usage with Hermes¶
Trigger the skill for any observability task:
"Set up application monitoring for our Node.js API"
"Add structured logging to the Python service"
"Create a Grafana dashboard for API latency"
"Run a load test against production with k6"
"Profile CPU/memory bottlenecks in the worker process"
"Define alerting rules for 5xx error rates"
Example: Setting Up API Monitoring¶
"Configure Prometheus metrics for our Express.js API - track request rate, error rate, and p95 latency"
The skill instruments the application with appropriate metrics libraries, configures scrape endpoints, builds Grafana dashboards, and defines alerting rules.
Core Capabilities¶
| Capability | Tools/Frameworks |
|---|---|
| Metrics collection | Prometheus, OpenTelemetry |
| Visualization | Grafana, Datadog |
| Logging pipelines | Structured logging, log shippers |
| Distributed tracing | OpenTelemetry, Jaeger |
| Load testing | k6, Artillery |
| Profiling | CPU/memory profilers |
| Capacity planning | Trend analysis, forecasting |
Guardrails¶
- Always verify data arrives before building dashboards
- Use RED method for services, USE method for resources
- Alert on symptoms, not causes
- Never alert on raw metrics without aggregation windows
Related Skills¶
- AWS Agent Toolkit Setup - AWS infrastructure monitoring
- Sentry AI Monitoring Setup - Error tracking
- HashiCorp Agent Skills Setup - Infrastructure management
Source¶
- skills.sh: jeffallan/claude-skills@monitoring-expert
- GitHub: github.com/jeffallan/claude-skills
Integration with CorpusIQ¶
CorpusIQ is the connector layer that lets AI assistants read the systems a business already runs on - accounting, payments, CRM, email, files and analytics - and answer with the source named. It is read-only by design: it retrieves data and never writes to, or acts in, a connected system, which is what makes it safe to point at live accounts.
This page is part of the CorpusIQ directory, the reference we maintain for the MCP server and agent-skill ecosystem. Run alongside CorpusIQ, a third-party server like this one can be combined with a company's own business data in a single answer.