How does this skill improve production reliability?

It identifies missing telemetry, silent failures, and inadequate error context during the code review phase, ensuring developers have the data needed to debug issues immediately upon deployment.

What kind of metrics does it recommend?

It focuses on the 'Golden Signals' including success/failure counters, latency histograms, saturation gauges, and rate metrics.

Can it detect sensitive data in logs?

Yes, the skill specifically checks for PII and secrets (like passwords or tokens) in logging statements to prevent security leaks in your monitoring pipelines.

Is this skill specific to a certain programming language?

No, it is designed to provide language-agnostic observability patterns and best practices applicable to most modern backend and full-stack environments.

Code Review Observability

Name: Code Review Observability
Author: xinbenlv

byxinbenlv

0•

分析と監視

Reviews code for logging, metrics, tracing, and alerting to ensure systems are observable, debuggable, and production-ready.

The Code Review Observability skill acts as a specialized SRE and Observability Engineer within your Claude Code environment. It systematically audits pull requests and source code for operational excellence, focusing on logging quality, metrics coverage, and distributed tracing. By identifying missing signals, improper log levels, and unmonitored failure modes before they reach production, this skill helps teams reduce MTTR and ensures that every new feature is built with a 'monitor-first' mindset.

主な機能

01Alertability assessment to identify silent failures and missing runbook hints.

02Comprehensive metrics coverage analysis for success, failure, and latency signals.

03Categorized reporting of observability gaps with actionable remediation steps.

040 GitHub stars

05Distributed tracing verification to ensure context propagation across services.

06Structured logging validation and PII/Secret detection in log streams.

ユースケース

01Reviewing backend pull requests to ensure new features are properly instrumented.

02Verifying that distributed microservices correctly propagate correlation IDs.

03Auditing legacy codebases to improve diagnostic signals and reduce log noise.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add xinbenlv/codereview-skills codereview-observability

For use in Claude.ai and ChatGPT

Download Skill