Skill UI

Guides setting up modern Python projects with uv, ruff, ty, pytest, prek, and security checks, covering initialization, pyproject configuration, dependency and tool management, quick-start scripts, full project layout, and migrations from legacy tooling.

A comprehensive skill set for building robust, type-safe, and highly performant Python 3.11+ applications. This specialist enforces best practices by generating type-annotated code, utilizing async/await patterns, structured dataclasses, and comprehensive error handling. The workflow mandates rigorous validation using tools like mypy (strict mode), black, ruff, and extensive pytest test suites to ensure code quality and reliability.

A comprehensive solution for identifying and preventing the accidental commitment of exposed AWS credentials, API keys, and session tokens within source code, configuration files, and git history. It integrates TruffleHog and git-secrets into CI/CD pipelines and pre-commit hooks, providing critical protection against credential theft and unauthorized cloud access in a DevSecOps environment. Essential for security auditing and compliance.

This skill guides the integration of gitleaks and trufflehog into CI/CD pipelines. It automates the detection of hardcoded secrets, such as API keys, passwords, and tokens, preventing their accidental deployment. By integrating scans as a mandatory pre-deployment gate, organizations enforce strong security policies and maintain compliance.

This advanced skill automates the enforcement of Python code quality using Ruff. It implements a controlled, iterative workflow that supports safe and unsafe automatic autofixes, formats the code, and reviews diffs after each pass. The process recursively repeats until all findings are resolved or require explicit user decision, ensuring high code consistency and quality gates.

This meta-skill runs three essential quality gates (ruff, mypy, and pytest) concurrently against the staged changes. It provides a comprehensive, CI-like check locally, offering a single BLOCK or APPROVE verdict to ensure code readiness before committing. It combines static analysis, type checking, and unit testing into one workflow.

This guide outlines a comprehensive workflow for detecting and preventing the exposure of sensitive AWS credentials (access keys, session tokens) within source code repositories, CI/CD pipelines, and configuration files. It utilizes TruffleHog for deep historical scanning and integrates git-secrets for robust pre-commit hooks, significantly reducing the risk of credential theft and unauthorized account access.

A comprehensive, multi-phase checklist for ensuring the quality, security, and deployment readiness of Django applications. It covers linting (ruff, mypy), unit testing (pytest), database migrations, security audits (bandit, pip-audit), and performance checks, making it an essential quality gate for CI/CD pipelines before merging or deploying to production.