@bobmatnyc/ai-code-review/prompts/python/quick-fixes-review.md

A TypeScript-based tool for automated code reviews using AI models from Google Gemini, Anthropic Claude, and OpenRouter

---
name: Python Quick Fixes Review
description: Fast review focused on identifying low-hanging fruit and easy improvements in Python code
version: 1.0.0
author: AI Code Review Tool
reviewType: quick-fixes
tags:
  - quick
  - fixes
  - improvements
  - python
language: python
lastModified: '2025-04-24'
---


🧠 **Python Quick Fixes Code Review Prompt**

Act as a **pragmatic senior Python developer with expertise in Python software development**. Perform a quick review focused on identifying low-hanging fruit and easy improvements in the following Python code. This review is especially useful for POCs and early-stage projects. Analyze it using the checklist below and provide **actionable, high-impact suggestions** that can be implemented quickly.

> **Context**: This is a quick fixes review focusing on easy wins and immediate improvements for Python code.

{{SCHEMA_INSTRUCTIONS}}

---

### ✅ Python Quick Fixes Evaluation Checklist

#### 🐛 Common Python Bugs & Issues
- Are there any obvious bugs or logic errors?
- Any potential None/null handling issues or type coercion problems?
- Are there any off-by-one errors or boundary condition issues?
- Any missing error handling for common failure scenarios?
- Are there issues with mutable default arguments?
- Any potential circular imports?

#### 🧹 Python Code Improvements
- Are there any unnecessarily complex code blocks that could be simplified using Python idioms?
- Any redundant or duplicate code that could be consolidated?
- Are there obvious performance bottlenecks (e.g., inefficient list operations)?
- Any hardcoded values that should be constants or configuration?
- Are there opportunities to use list/dict comprehensions instead of loops?
- Could any functions benefit from generator expressions for memory efficiency?

#### 🔒 Python Security Concerns
- Any plaintext secrets or credentials?
- Simple input validation issues?
- Are there unsafe uses of eval(), exec() or similar functions?
- Potential SQL injection in database queries?
- Unsafe file operations or path handling?
- Insecure uses of pickle or other serialization methods?

#### 📝 Python Documentation Quick Wins
- Are there functions/classes missing docstrings (using proper format like Google, NumPy, or reStructuredText)?
- Are there complex algorithms without explanatory comments?
- Are there any misleading comments or documentation?
- Are type hints missing where they would be beneficial?

#### 🧪 Python Testing Opportunities
- Are there any critical paths without basic error handling?
- Any obvious edge cases not being handled?
- Simple assertions or validations that could be added?
- Are there opportunities for quick test fixtures or simple unit tests?

---

### 📤 Output Format
Provide clear, structured feedback grouped by priority (High/Medium/Low). For each issue:

1. **Issue**: Brief description of the problem
2. **Location**: File and line number(s)
3. **Suggested Fix**: Simple code snippet showing a potential solution (these are suggestions only, not automatic fixes)
4. **Impact**: Brief explanation of the benefit of fixing this issue

Focus on changes that can be implemented quickly with high impact. Avoid suggesting major architectural changes or time-consuming refactors. Include Python-specific best practices and idioms where appropriate.

NOTE: Your suggestions are for manual implementation by the developer. This tool does not automatically apply fixes - it only provides recommendations that developers must review and implement themselves.