log-analysis

Analyzes Node.js app logs for errors and traces requests via Swim-lane IDs.

1|Updated Mar 6, 2026

Search Tags:#debugging #logging #observability #node.js #distributed systems #incident response

Ready to run

npx skills add https://github.com/chavangorakh1999/sde-skills --skill log-analysis-chavangorakh1999

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: log-analysis
Source: https://github.com/chavangorakh1999/sde-skills/tree/main/sde-debugging/skills/log-analysis
Command: npx skills add https://github.com/chavangorakh1999/sde-skills --skill log-analysis-chavangorakh1999

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you efficiently investigate incidents by providing strategies for parsing logs, tracing requests across distributed systems, and identifying failure modes.

Core Features & Use Cases

Structured Logging: Guides you on implementing and leveraging structured logs for better queryability.
Correlation ID Tracing: Explains how to use correlation IDs to follow a request's journey through multiple services.
Log Query Patterns: Offers specific query examples for common issues like error spikes, slow requests, and authentication failures.
Use Case: When a critical API endpoint is failing intermittently, use this Skill to analyze logs, trace the problematic requests using correlation IDs, and pinpoint the service or specific log pattern causing the errors.

Quick Start

Use the log-analysis skill to find the root cause of the recent production incident by analyzing the provided logs.

Frequently Asked Questions about log-analysis

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

FAQPage Schema

How do I trace a request across distributed Node.js services using logs?▼

To trace a request across distributed Node.js services, you implement correlation ID tracing to follow the request's journey through multiple services. This allows you to track how data flows and identify failure points across the system.

What are the best query patterns to find error spikes and slow requests in application logs?▼

The best query patterns to find error spikes and slow requests involve querying structured logs for specific failure signatures. You search for error rate anomalies and latency thresholds to pinpoint problematic requests and identify the service causing the errors.

How does structured logging improve incident response debugging?▼

Structured logging improves incident response debugging by providing better log queryability. It enables automated parsing and specific query patterns for common issues like authentication failures, making it faster to extract actionable insights during an incident.

Can I use this log analysis approach for intermittent API endpoint failures in production?▼

Yes, you can use this log analysis approach for intermittent API endpoint failures. It guides you to analyze production logs, trace problematic requests using correlation IDs, and pinpoint the specific service or log pattern causing the errors.

What should I consider when setting log retention policies for distributed systems?▼

When setting log retention policies for distributed systems, you should consider balancing storage costs with the need for historical data during incident investigation. This Skill provides guidance on configuring policies to ensure logs remain available for reconstructing distributed traces.

Why do I need correlation IDs to investigate Node.js incidents?▼

You need correlation IDs to investigate Node.js incidents because they allow you to reconstruct distributed traces. By attaching a unique identifier to each request, you can follow its journey across multiple services and isolate the exact point of failure.