Does it cover interactive debugging?

Yes, it covers the built-in pdb module, the enhanced ipdb debugger, and techniques for post-mortem debugging after an exception occurs.

Can I use this for performance optimization?

Absolutely, the skill includes guidance for using cProfile, line_profiler, and memory_profiler to identify and resolve performance bottlenecks.

How does this help with log management?

It outlines best practices for log levels, avoiding sensitive data leaks, and implementing lazy formatting to ensure logs are both useful and efficient.

Does this skill support structured logging?

Yes, it provides detailed implementations for JSON logging and context-aware logs using the python-json-logger library and standard logging filters.

Are there visual profiling tools included?

The skill provides patterns for using py-spy to generate flamegraphs and Rich for beautiful, readable tracebacks in the console.

Observability & Debugging

Name: Observability & Debugging
Author: akaszubski

byakaszubski

•

Analíticas y Monitorización

Implements advanced logging, interactive debugging, and performance profiling patterns to enhance application visibility and reliability.

Acerca de

The Observability skill is a comprehensive guide for developers looking to instrument their applications for better monitoring and faster troubleshooting. It provides standardized patterns for structured JSON logging, context-aware log management, and interactive debugging using tools like pdb and ipdb. Beyond basic logging, it offers detailed strategies for CPU and memory profiling to identify performance bottlenecks and leaks, ensuring that Claude can assist in creating production-ready, highly maintainable codebases.

Características Principales

Memory usage tracking and leak detection patterns
2 GitHub stars
Interactive and post-mortem debugging with pdb and ipdb
Enhanced stack trace visualization and context logging
CPU profiling using cProfile and line-by-line analysis
Structured JSON logging implementation for log aggregators

Casos de Uso

Setting up automated debugging environments for uncaught exceptions
Diagnosing and fixing slow API endpoints using performance profilers
Instrumenting a new service with production-grade structured logging

Acerca de

Características Principales

Memory usage tracking and leak detection patterns
2 GitHub stars
Interactive and post-mortem debugging with pdb and ipdb
Enhanced stack trace visualization and context logging
CPU profiling using cProfile and line-by-line analysis
Structured JSON logging implementation for log aggregators

Casos de Uso

Setting up automated debugging environments for uncaught exceptions
Diagnosing and fixing slow API endpoints using performance profilers
Instrumenting a new service with production-grade structured logging