pythonista-reviewing

Name: pythonista-reviewing
Availability: InStock
Author: Gigaverse

Identify egregious code-quality issues in GitHub pull requests and diffs.

4|Updated Jan 16, 2026

Search Tags:#llm #diff #guidelines #pr #best-practices #code-review

Ready to run

npx skills add https://github.com/gigaverse-app/skillet --skill pythonista-reviewing

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: pythonista-reviewing
Source: https://github.com/gigaverse-app/skillet/tree/main/pythonista/skills/pythonista-reviewing
Command: npx skills add https://github.com/gigaverse-app/skillet --skill pythonista-reviewing

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Use when reviewing code, PRs, or diffs. Triggers on "review", "code review", "PR", "pull request", "diff", "check this", "look at this code", "quality", "refactor", "egregious", "cross-file", "duplicate", "duplication", or when examining code for issues.

Core Features & Use Cases

Structured, best-practice prompts to guide code review of diffs and PRs
LLM-assisted detection of cross-file patterns and architectural concerns
Reference materials and related skills to extend and tailor reviews

Quick Start

Submit the PR diff to the AI reviewer and let the built-in prompts generate an egregious-issues report.

Frequently Asked Questions about pythonista-reviewing

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I use AI to review a GitHub pull request for code quality?▼

AI-assisted code review analyzes your GitHub pull request diffs using structured LLM prompts to identify egregious code-quality issues. You submit the PR diff, and the built-in best-practice workflow generates a targeted issues report.

What is the best way to detect cross-file duplication and architectural issues in a diff?▼

Detecting cross-file duplication in a diff requires analyzing patterns across multiple files simultaneously. LLM-assisted code review workflows use structured prompts to evaluate cross-file quality checks, identifying architectural concerns and duplicated logic.

Can I trigger an automated code review workflow by asking it to check my code?▼

Automated code review workflows can be triggered by natural language commands like "review", "check this", or "look at this code". This initiates the LLM-assisted analysis to examine your code diffs for egregious quality issues.

Does AI-guided code review work with existing GitHub PRs and standard diff formats?▼

AI-guided code review workflows apply directly to standard GitHub PRs and diff formats. The structured LLM prompts process these inputs to evaluate cross-file quality checks and generate best-practice compliance reports.

What are the limitations of using LLM prompts for code review?▼

LLM-assisted code review focuses specifically on identifying egregious code-quality issues rather than providing comprehensive architectural overhauls. It augments human review workflows by targeting cross-file patterns and duplication using structured prompts.

Do I need to configure scripts and references before starting an AI code review?▼

AI code review workflows integrate optional resources like scripts and references to extend analysis capabilities. The core functionality operates using built-in best-practice prompts applied directly to your PR diffs without mandatory external setup.