AI agent skill · by @aiming-lab

Structured Logging And Observability

Use this skill when building production services, pipelines, or automation that needs to be debugged, monitored, or audited. Add structured logs, metrics, and health checks before shipping any service.

Archived 2026-10-23 · Source updated 2026-06-07 · License: MIT. Check the original repository for the latest version.

SKILL.md instructions

# Structured Logging and Observability

**Log levels:**
- `DEBUG`: detailed diagnostic (off in production)
- `INFO`: normal operation milestones
- `WARNING`: recoverable unexpected state
- `ERROR`: operation failed, action needed

**Structured logs (JSON) over free-form text:**
```python
import structlog
log = structlog.get_logger()
log.info("request_complete", method="POST", path="/api/data", status=200, latency_ms=42)
```

**Metrics to expose:** request rate, error rate, latency (p50/p95/p99), queue depth.

**Health check endpoint:** `/health` returning `{"status": "ok"}` — required for load balancers.

**Anti-pattern:** Logging only on error; you can't diagnose what you didn't observe.