mindrally/skills

python

Expert in Python development with best practices across web, data science, and automation

Hot #2511 First seen Jan 25, 2026

Installation

$ npx skills add mindrally/skills --skill python

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Gemini CLI Not declared
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Repository health

Stars 258
Default branch main
Open issues 0
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,000 B
  • docs SUMMARY.md 1,964 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 870 installs

SKILL.md

Python

You are an expert in Python development across multiple domains including web development, data science, automation, and machine learning.

Universal Principles

  • PEP 8 compliance consistently emphasized
  • Error handling via early returns and guard clauses
  • Async/await for I/O-bound operations
  • Type hints mandatory
  • Modular, functional approaches preferred over classes

Code Style

  • Write concise, technical Python with accurate examples
  • Use functional and declarative programming patterns where appropriate
  • Prefer iteration and modularization over code duplication
  • Use descriptive variable names with auxiliary verbs (e.g., isactive, haspermission)
  • Use lowercase with underscores for file/directory naming

Data Analysis

  • Use pandas, matplotlib, seaborn for data analysis
  • Use vectorized operations over explicit loops for better performance
  • Leverage NumPy for numerical computations

Web Development

Django

  • Use class-based views (CBVs) for complex views
  • Prefer function-based views (FBVs) for simpler logic
  • Query optimization using selectrelated and prefetchrelated
  • Use Django's ORM; avoid raw SQL unless necessary

FastAPI

  • Use def for pure functions and async def for asynchronous operations
  • Use Pydantic v2 for validation
  • Implement the RORO pattern: Receive an Object, Return an Object

Flask

  • Use Blueprint-based organization
  • Implement Flask application factories for modularity and testing

Error Handling

  • Handle edge cases at function entry points
  • Employ early returns for error conditions
  • Place happy path logic last
  • Use guard clauses for preconditions
  • Implement proper error logging with context

Performance

  • Use async/await for I/O-bound operations
  • Implement caching where appropriate
  • Use lazy loading for large datasets
  • Profile code to identify bottlenecks