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observability-review

Review application observability for gaps in logs, metrics, traces, and alerting.

Updated May 10, 2026
Search Tags:#logging#metrics#observability#tracing#alerting#opentelemetry#structured logging
One-click install
npx skills add https://github.com/rob-broadley/ai-airbase --skill observability-review-rob-broadley
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: observability-review
Source: https://github.com/rob-broadley/ai-airbase/tree/main/cadre/skills/observability-review
Command: npx skills add https://github.com/rob-broadley/ai-airbase --skill observability-review-rob-broadley

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you evaluate whether an application’s observability signals—logs, metrics, traces, and alerts—are complete, consistent, and useful enough for operators to detect, diagnose, and recover quickly.

Core Features & Use Cases

  • Log level and quality review: checks DEBUG/INFO/WARN/ERROR usage to avoid noisy or missing signal during production incidents.
  • Structured logging and trace context validation: ensures logs are queryable (key-value), do not leak PII/secrets, and include correlation/trace IDs for end-to-end debugging.
  • Metrics, alerting, and naming guidance: verifies metric naming conventions, prevents high-cardinality label explosions, and assesses alert quality using a severity model tied to operator actionability.

Quick Start

Ask an AI agent to perform an observability review for your codebase, explicitly focusing on log levels, structured logging, trace propagation, metric naming, and alert quality against the observability-review guidelines.

Frequently Asked Questions about observability-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
What is observability review and why do I need it for my application?▼

To review structured logging, verify your logs use consistent key-value formats with stable field names, avoid leaking PII or secrets, and include trace or correlation IDs for end-to-end debugging across distributed system boundaries.

How do I prevent high-cardinality metrics and alert noise during incidents?▼

Yes, observability review applies to distributed systems and background jobs by validating OpenTelemetry semantic conventions, trace context propagation, and consistent queryable signals across service boundaries.

How do I review log levels to avoid noisy or missing signals during incidents?▼

Review log levels by checking DEBUG, INFO, WARN, and ERROR usage throughout your service code to ensure appropriate signal volume, preventing noisy logs from obscuring critical errors or missing context during production incidents.

What are the limitations of observability review for microservices?▼

Observability review relies on existing application code and cannot generate missing telemetry automatically. It requires structured logging and OpenTelemetry conventions to already be partially implemented to provide meaningful gap analysis.

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