Python Performance Profiler
- 193 installs
- 2 repo stars
- Updated January 25, 2026
- jorgealves/agent_skills
Profile CPU, memory, and I/O hotspots in Python apps using cProfile, py-spy, and tracing to fix regressions before latency SLO breaches in production.
About
Profiles Python applications to locate CPU, memory, and I/O bottlenecks using standard profilers and tracing, then recommends targeted fixes so APIs and services meet latency and throughput targets before ship.
- cProfile and py-spy usage
- CPU and memory hotspots
- I/O bottleneck tracing
- Regression diagnosis
- SLO-oriented tuning
Python Performance Profiler by the numbers
- 193 all-time installs (skills.sh)
- +12 installs in the week ending Aug 2, 2026 (Skillselion tracking)
- Ranked #176 of 596 Debugging skills by installs in the Skillselion catalog
- Data as of Aug 2, 2026 (Skillselion catalog sync)
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| Installs | 193 |
|---|---|
| repo stars | ★ 2 |
| Last updated | January 25, 2026 |
| Repository | jorgealves/agent_skills ↗ |
What it does
Profile CPU, memory, and I/O hotspots in Python apps using cProfile, py-spy, and tracing to fix regressions before latency SLO breaches in production.
Files
Python Performance Profiler
Purpose and Intent
Identify CPU and memory bottlenecks in Python code using cProfile or memory_profiler. Use to optimize mission-critical Python services.
When to Use
- Project Setup: When initializing a new Python project.
- Continuous Integration: As part of automated build and test pipelines.
- Legacy Refactoring: When updating older Python codebases to modern standards.
When NOT to Use
- Non-Python Projects: This tool is specialized for the Python ecosystem.
Error Conditions and Edge Cases
- Missing Requirements: If the project lacks a requirements.txt or pyproject.toml.
- Incompatible Versions: If the project uses a Python version not supported by the tools.
Security and Data-Handling Considerations
- All analysis is performed locally.
- No source code or credentials are ever transmitted externally.
name: python-performance-profiler
version: 1.0.0
description: Identify CPU and memory bottlenecks in Python code using cProfile or memory_profiler. Use to optimize mission-critical Python services.
inputs:
project_path:
type: string
description: Path to the Python project directory.
required: true
outputs:
report:
type: string
description: A detailed report of the analysis or actions performed.
capabilities:
- Automated analysis of Python project structure.
- Integration with standard Python tooling.
constraints:
- Requires a valid Python environment.
security:
- Operates locally on source files.
examples:
- input:
project_path: "."
output:
report: "Analysis complete. No issues found."
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