Can I use this for AWS CloudWatch or Azure Monitor?

No, this specific skill is purpose-built for Google Cloud Logging and relies on the gcloud CLI and GCP-specific log structures.

What prerequisites are needed to use this skill?

You must have the gcloud CLI, jq, and DuckDB installed on your system, and you must be authenticated via 'gcloud auth login' with appropriate permissions to read logs in your target project.

What is the advantage of using this skill over the GCP Console?

This skill allows for faster, scriptable analysis using powerful local tools like jq and DuckDB. It enables complex aggregations, cross-referencing, and multi-step investigation workflows that are often cumbersome in a web-based UI.

How does it handle large log volumes?

It follows a best-practice workflow: first verifying log structure with small samples, then using indexed fields for efficient filtering, and finally downloading specific datasets to local files for fast, iterative processing.

GCP Logging Investigator

Name: GCP Logging Investigator
Author: pokutuna

bypokutuna

0•

Analytics & Monitoring

Investigates and analyzes Google Cloud logs using gcloud CLI, jq, and DuckDB for deep performance and error insights.

This skill empowers developers to efficiently query, filter, and analyze Google Cloud Logging data directly through the gcloud CLI. It streamlines the debugging process by exporting logs to local files for iterative analysis, utilizing indexed fields for performance, and applying specialized jq filters for common tasks like latency analysis, trace tracking, and error pattern recognition. Whether troubleshooting a 500 error in GKE or performing percentile latency analysis on Cloud Run, this skill provides a structured workflow for data-driven observability and rapid root-cause identification.

Key Features

01High-performance log aggregation and SQL-based querying via DuckDB integration

020 GitHub stars

03Pre-built jq scripts for error analysis, latency distribution, and audit log visualization

04Automated log retrieval using gcloud logging read with built-in timeout protections

05Advanced filtering using indexed fields like resource.type, severity, and trace ID for high performance

06Structured investigation workflow from initial context gathering to final summary reports

Use Cases

01Troubleshooting production 500 errors by extracting and analyzing stack traces across GKE or Cloud Run

02Tracing specific request flows across microservices using trace ID correlation and chronological sorting

03Identifying API performance bottlenecks through P50, P95, and P99 latency percentile analysis

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add pokutuna/claude-plugins investigate-logging

For use in Claude.ai and ChatGPT

Download Skill