common-observability

Enforce structured JSON logging, OpenTelemetry distributed tracing, and RED metrics across backend services. Use when adding request correlation, setting up tracing spans, defining SLO burn-rate alerts, or instrumenting middleware. (triggers: **/*.service.ts, **/*.handler.ts, **/*.middleware.ts, **/*.interceptor.ts, **/*.go, **/*.java, **/*.kt, **/*.py, logging, tracing, metrics, opentelemetry, observability, slo)

385 stars

Best use case

common-observability is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Enforce structured JSON logging, OpenTelemetry distributed tracing, and RED metrics across backend services. Use when adding request correlation, setting up tracing spans, defining SLO burn-rate alerts, or instrumenting middleware. (triggers: **/*.service.ts, **/*.handler.ts, **/*.middleware.ts, **/*.interceptor.ts, **/*.go, **/*.java, **/*.kt, **/*.py, logging, tracing, metrics, opentelemetry, observability, slo)

Teams using common-observability 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

$curl -o ~/.claude/skills/common-observability/SKILL.md --create-dirs "https://raw.githubusercontent.com/HoangNguyen0403/agent-skills-standard/main/skills/common/common-observability/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/common-observability/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How common-observability Compares

Feature / Agentcommon-observabilityStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Enforce structured JSON logging, OpenTelemetry distributed tracing, and RED metrics across backend services. Use when adding request correlation, setting up tracing spans, defining SLO burn-rate alerts, or instrumenting middleware. (triggers: **/*.service.ts, **/*.handler.ts, **/*.middleware.ts, **/*.interceptor.ts, **/*.go, **/*.java, **/*.kt, **/*.py, logging, tracing, metrics, opentelemetry, observability, slo)

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

# Common Observability Standards

## **Priority: P1 (OPERATIONAL)**

## Logging & Tracing

- **JSON Logs**: Always emit JSON structured logs. Never plain-text in prod.
- **Correlation**: Extract `X-Request-Id` or `traceparent`. Attach to async context.
- **Tracing**: Use OpenTelemetry. Propagate W3C `traceparent`.
- **Spans**: Name spans like `<HTTP_METHOD> <route>` (`GET /users/:id`).

See [implementation examples](references/implementation.md) for structured logger setup with Pino.

## Metrics

- **Required**: Request rate, Error rate, Latency histogram (p50/p95/p99), Saturation.
- **SLOs**: Alert on SLO burn rates, not raw threshold spikes.

## Anti-Patterns

- **Console.log**: Do not use in prod; use a structured logger (`pino`, `zap`).
- **PII in Logs**: Never log tokens, passwords, or full request bodies.
- **Dynamic Span Names**: `GET /users/123` causes cardinality explosion. Use `GET /users/:id`.
- **Missing Cleanup**: Always end tracing spans.

## References
- [Observability Data Formats](references/observability-formats.md)

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