Skill UI

This skill automates the creation of comprehensive test suites for any codebase. Utilizing advanced AI capabilities, it analyzes function signatures, automatically identifies potential edge cases, generates meaningful assertions, and produces necessary mock data and fixture files. It is essential for developers needing robust unit tests, increasing code coverage, and adopting Test-Driven Development (TDD) workflows across various frameworks like Jest or pytest.

A comprehensive guide for upgrading Windsurf IDE to new versions and migrating settings, extensions, and configurations from competing editors like VS Code or Cursor. It details manual migration steps, handles breaking changes, and introduces Windsurf-specific features like Cascade Workflows and Turbo Mode.

This skill guides the development of custom extensions for the Windsurf environment, leveraging the full VS Code Extension API. You will learn to track various workspace events—such as file saves, editor changes, and terminal outputs—and integrate this data with external services by sending structured webhooks. This is essential for building complex workflow automation, implementing custom IDE features, or creating data analytics tools within the development lifecycle.

Automates zero trust configuration support for advanced security operations, offering guidance, code/config generation, and validation whenever zero trust config helper topics arise during penetration testing, compliance, or threat modeling workflows.

Audits GitHub Actions workflows that invoke AI coding agents to surface prompt injection and sandbox risks, tracing attacker-controlled inputs through env vars, reusable actions, and workflow references before deployment or code review.

Detects missing zeroization of secrets and flags compiler-optimized removals with mandatory assembly/IR evidence, helping auditors verify C/C++/Rust cryptographic code through dataflow, CFG, and runtime validation.

Guides engineers through a disciplined four-phase debugging workflow so they investigate root causes, analyze patterns, test hypotheses, and implement fixes based on evidence before touching code.

This model provides an engineering operational framework for teams that leverage AI agents to generate large volumes of code. It shifts the focus from simple syntax to process quality, robust architecture design, rigorous testing, and systematic risk control, ensuring the development of highly stable and reliable systems in AI-assisted environments.

This skill helps users create a new Git branch that strictly adheres to established project naming conventions (e.g., Sentry standards). It automatically determines the appropriate branch type (such as `feat`, `fix`, `chore`, etc.) and generates a descriptive, standardized branch name by analyzing the provided work description or local code differences (diff). It guides the entire branching workflow, ensuring proper lineage and classification for code submissions.

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.

Use this guide to build and manage Expo development clients using EAS Build. This is the recommended setup for production-grade testing, allowing developers to test custom native code, local modules, and advanced features that exceed Expo Go's capabilities. It covers local builds, TestFlight submission, and connecting to the Metro bundler.

Learn how to handle errors in TypeScript using functional patterns like `Either` and `TaskEither`, eliminating messy try/catch blocks. This guide teaches that errors are simply data, allowing you to write cleaner, more predictable, and type-safe code that explicitly handles potential failures through explicit return values.