observability-instrumentation
Use when adding endpoints/background jobs/integrations where telemetry matters. Do NOT refactor unrelated code. Prefer OpenTelemetry-friendly patterns.
Best use case
observability-instrumentation is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Use when adding endpoints/background jobs/integrations where telemetry matters. Do NOT refactor unrelated code. Prefer OpenTelemetry-friendly patterns.
Teams using observability-instrumentation should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/observability-instrumentation/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How observability-instrumentation Compares
| Feature / Agent | observability-instrumentation | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Use when adding endpoints/background jobs/integrations where telemetry matters. Do NOT refactor unrelated code. Prefer OpenTelemetry-friendly patterns.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
Principles: - Low-cardinality metrics labels. - Structured logs with correlation IDs; never log secrets. - Trace the "edges": inbound request, outbound calls, key domain operations. Checklist: - Tracing - Create spans around external calls (HTTP, DB, message bus, 3rd party SDK) - Add useful span attributes (route, status code, dependency name) - Propagate context across async boundaries and between services - Metrics - Add counters for throughput and errors - Add histograms for latency where needed - Avoid user IDs, request IDs, or other high-cardinality labels - Logging - Structured logging (message templates) - Correlation/trace IDs included (or derived from OTel) - Redaction of PII/secrets - Health & readiness - Ensure health endpoints or probes reflect real dependencies (as per repo convention) - Verification - Verify local export path (console/OTLP) and sample traces appear - Add minimal docs: how to run locally + where to look in dashboards Finish with: - What telemetry was added (spans/metrics/logs) - How to validate locally - Risks (cardinality, PII, perf)
Related Skills
observability-monitoring-performance-engineer
Expert performance engineer specializing in modern observability, application optimization, and scalable system performance. Masters OpenTelemetry, distributed tracing, load testing, multi-tier caching, Core Web Vitals, and performance monitoring. Handles end-to-end optimization, real user monitoring, and scalability patterns. Use PROACTIVELY for performance optimization, observability, or scalability challenges. Use when: the task directly matches performance engineer responsibilities within plugin observability-monitoring. Do not use when: a more specific framework or task-focused skill is clearly a better match.
Implementing Observability
Instrument the application with Logging, Metrics, and Tracing (OpenTelemetry) to understand system behavior and debug production issues.
observability-review
AI agent that analyzes operational signals (metrics, logs, traces, alerts, SLO/SLI reports) from observability platforms (Prometheus, Datadog, New Relic, CloudWatch, Grafana, Elastic) and produces practical, risk-aware triage and recommendations. Use when reviewing system health, investigating performance issues, analyzing monitoring data, evaluating service reliability, or providing SRE analysis of operational metrics. Distinguishes between critical issues requiring action, items needing investigation, and informational observations requiring no action.
api-testing-observability-api-mock
You are an API mocking expert specializing in realistic mock services for development, testing, and demos. Design mocks that simulate real API behavior and enable parallel development.
bgo
Automates the complete Blender build-go workflow, from building and packaging your extension/add-on to removing old versions, installing, enabling, and launching Blender for quick testing and iteration.
poetry-rye-dependency-management
Specifies Poetry or Rye for dependency management in Python projects.
podcastfy-clawdbot
Generate an AI podcast (MP3) from one or more URLs using the open-source Podcastfy project. Use when the user says “make a podcast from this URL/article/video/PDF”, “turn this webpage into a podcast”, or wants an MP3 conversation-style summary from links. Uses Gemini for transcript generation via GEMINI_API_KEY and Edge TTS for free voice.
plugin-patterns
Canvas plugin architecture patterns, best practices, and implementation templates
playwright-skill
Complete browser automation with Playwright. Auto-detects dev servers, writes clean test scripts to /tmp. Test pages, fill forms, take screenshots, check responsive design, validate UX, test login flows, check links, automate any browser task. Use when user wants to test websites, automate browser interactions, validate web functionality, or perform any browser-based testing.
playwright-core
Battle-tested Playwright patterns for E2E, API, component, visual, accessibility, and security testing. Covers locators, assertions, fixtures, network mocking, auth flows, debugging, and framework recipes for React, Next.js, Vue, and Angular. TypeScript and JavaScript.
playwright-app-testing
Test the Expensify App using Playwright browser automation. Use when user requests browser testing, after making frontend changes, or when debugging UI issues
platform-engineer
**Master Skill**: Unified Platform, SRE & Release Engineering. Covers OpenShift 4.20+, GitOps (ArgoCD/Tekton), Container Hardening, Service Mesh, Feature Flags, Progressive Rollouts, Observability (LGTM Stack), Chaos Engineering, and Disaster Recovery.