How does this skill improve application performance?

It provides timing decorators and context manager timers to measure execution duration, enabling developers to find and fix slow code blocks effectively.

Does it support interactive debugging during development?

Absolutely. It contains a comprehensive cheat sheet for pdb and ipdb commands, as well as strategies for post-mortem debugging after a crash.

Are there best practices for error isolation?

Yes, the skill covers tactical debugging strategies like Binary Search Debugging and Rubber Duck Debugging to help isolate issues in complex codebases.

Can this skill help with structured logging?

Yes, it provides implementation patterns for JSON-formatted logs, including metadata context and appropriate log-level management for production environments.

What Python profiling tools does this skill support?

The skill includes guidance for cProfile (CPU profiling), line_profiler (line-by-line analysis), memory_profiler (memory usage), and py-spy (sampling profiling).

Python Observability & Debugging

Name: Python Observability & Debugging
Author: akaszubski

byakaszubski

•

Analytics & Monitoring

Implements structured logging, interactive debugging, and comprehensive performance profiling for Python applications.

This skill equips Claude with advanced diagnostic capabilities for Python development, focusing on structured logging, performance profiling, and interactive debugging techniques. It provides standardized patterns for JSON-based logging, memory and CPU usage analysis using tools like cProfile and line_profiler, and tactical debugging strategies using pdb/ipdb. By following these production-ready patterns, developers can identify bottlenecks, resolve complex bugs, and monitor application health with machine-readable diagnostics and rich context.

Key Features

01Structured JSON logging for machine-readable and searchable diagnostics

02Performance monitoring via timing decorators and custom metrics

0310 GitHub stars

04CPU and memory profiling using cProfile, line_profiler, and memory_profiler

05Interactive debugging patterns using pdb, ipdb, and post-mortem analysis

06Comprehensive guide to debugging strategies and logging anti-patterns

Use Cases

01Identifying and fixing performance bottlenecks in data-heavy applications

02Diagnosing intermittent production bugs using structured log context

03Standardizing logging and monitoring across multiple microservices

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add akaszubski/autonomous-dev observability

For use in Claude.ai and ChatGPT

Download Skill