
from awesome-skills-cn61
Profiles and optimizes Python code using CPU and memory profilers, actionable best practices, and a focused implementation playbook to reduce latency and resour
This skill provides a structured, practical workflow for profiling, diagnosing, and improving Python application performance. It covers CPU profiling, memory analysis, I/O optimization, database query tuning, and algorithmic improvements, and points to an implementation playbook with examples. The guidance emphasises measurable goals, reproducible profiling, and verification steps so changes are validated in real environments.
Use this skill when you need to identify and fix performance bottlenecks in Python services, reduce response latency, lower memory consumption or resolve memory leaks, speed up data-processing pipelines, or improve database-backed application throughput. Avoid using it for unrelated tasks like feature design or non-Python language performance work.
Best suited to agents and tooling that can run shell commands and examine code (Copilot-style or Claude Code agents) and developer workflows that can execute profilers and collect artifacts.
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