debugging

Analyze stack traces, logs, and performance data to identify root causes.

Updated Apr 12, 2026

Search Tags:#debugging #logs #memory #profiling #tracing #stack-trace

Ready to run

npx skills add https://github.com/gil00pita/lanify --skill debugging-gil00pita

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: debugging
Source: https://github.com/gil00pita/lanify/tree/main/.agents/skills/debugging
Command: npx skills add https://github.com/gil00pita/lanify --skill debugging-gil00pita

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Analyzes logs and traces to quickly diagnose failures, bottlenecks, and anomalies across distributed systems, reducing triage time and mean time to resolution.

Core Features & Use Cases

Stack-trace analysis with actionable insights
Log pattern detection, error clustering, and anomaly spotting
Performance and memory debugging guidance, including profiling workflows
Distributed tracing guidance and context propagation checks
Use Case: When a developer encounters cryptic errors, this skill analyzes stack traces and logs to propose root causes and recommended fixes.

Quick Start

Provide a quick diagnostic pass over your log file to generate a concise report and recommended next steps.

Frequently Asked Questions about debugging

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

FAQPage Schema

How do I analyze a stack trace to find the root cause of a crash?▼

To analyze a stack trace, review the anatomy of the call sequence to identify the failing function and originating module. This skill provides structured techniques to decode stack traces and propose actionable root causes for software crashes.

What is the best way to debug memory leaks and slow responses in microservices?▼

Debugging memory leaks and slow responses requires analyzing performance data and profiling workflows. This skill provides memory analysis guidance and profiling techniques to identify bottlenecks and anomalies across distributed microservice architectures.

How do I set up distributed tracing with OpenTelemetry for context propagation?▼

Setting up distributed tracing with OpenTelemetry involves configuring context propagation across microservice boundaries. This skill provides structured tracing setup guidance and checks to help diagnose failures and anomalies in distributed systems.

Can I use this to analyze logs and spot anomalies in Node.js, Python, Go, and Java runtimes?▼

Yes, you can analyze logs and spot anomalies across Node.js, Python, Go, and Java runtimes. The skill performs log pattern detection, error clustering, and anomaly spotting to reduce triage time across multiple supported environments.

Why should I use structured log analysis for diagnosing distributed system failures?▼

Structured log analysis identifies failure patterns and anomalies that manual review misses. By clustering errors and matching log patterns, this approach reduces mean time to resolution and quickly diagnoses bottlenecks across distributed systems.