Skill UI

A rigorous, security-focused code review process designed for Pull Requests (PRs), commits, and diffs. It moves beyond general reviews by focusing intensely on high-risk areas such as authentication, cryptography, external calls, and value transfer. The methodology is evidence-based, requiring detailed attack scenario modeling and generating comprehensive, auditable markdown reports to identify overlooked vulnerabilities and regressions.

This guide provides a deep, investigation-driven methodology for reviewing Django and Django REST Framework (DRF) codebases. It helps identify critical authorization gaps, focusing on Insecure Direct Object References (IDOR) and object-level access failures. Learn how to trace data flows, analyze custom managers, and verify that users can only access resources they are explicitly authorized to view or modify.

This skill provides comprehensive guidelines and automated checks for auditing and fixing HTML accessibility violations. It covers critical WCAG areas including proper ARIA labeling, full keyboard navigation support, focus management for modals and dialogs, color contrast adherence, and robust form error handling. Use it when developing any interactive UI component or reviewing existing code for accessibility compliance.

This skill fetches unread GitHub Pull Requests (PRs) that require review from a specified team or were opened by a team member. It is ideal for users who need to check their team's review queue, find PRs needing attention, or automate the process of reviewing open code submissions without manually browsing GitHub notifications. Requires GitHub CLI authentication.

Guides building custom Odoo modules by scaffolding manifests, models, views, and security rules, reviewing existing code, and applying ORM best practices across Community and Enterprise editions.

This guide outlines best practices for creating high-quality, structured pull requests (PRs) using Git and GitHub CLI. It ensures that every PR description captures not only what changed, but also the 'why' and necessary context for reviewers, significantly improving the code review process and adherence to engineering standards.

A set of behavioral guidelines derived from Andrej Karpathy's observations to help users writing, reviewing, or refactoring code with Large Language Models (LLMs). It guides developers to avoid overcomplication, make surgical changes, explicitly surface assumptions, and define verifiable success criteria, promoting clean, simple, and robust code development.

Handles QA code review reports by prioritizing critical and warning findings, implementing fixes with tests, running verification checklists, and preparing re-verification reports via the Forja Dev agent.

Aggregates Uncle Bob’s Clean Code, Architecture, Coder, Agile, and design-pattern guidance to evaluate reviews, refactors, and architecture decisions, and to surface professionalism heuristics without replacing your linter or formatter.

This skill provides a comprehensive framework for designing and reviewing native iOS applications. It covers adherence to Apple's Human Interface Guidelines (HIG), ensuring consistency across layout, typography, safe areas, and system components (e.g., Dynamic Island). Use this when building or reviewing SwiftUI/UIKit code to guarantee the app feels intuitive, highly polished, and genuinely native to the Apple ecosystem.

A powerful code review utility designed for SwiftUI projects. It comprehensively analyzes code quality, ensuring adherence to modern Swift APIs, optimal performance, robust data flow management, and compliance with Apple's Human Interface Guidelines and accessibility standards (like VoiceOver and Dynamic Type). Use this tool when writing, refactoring, or reviewing complex SwiftUI implementations to maintain high code hygiene and maintainability.

This skill orchestrates the entire coding lifecycle as a state machine, ensuring tasks proceed from issue intake through implementation, structured review, deployment, and final acceptance verification. It enforces a rigorous 'Definition of Done' (DoD) proof, moving beyond simple code changes. Ideal for complex feature development requiring structured handoffs and explicit verification evidence.