Skill UI

This guide outlines best practices for configuring IDEs and AI context management across complex, multi-service monorepos. It is essential for onboarding new teams, standardizing coding standards, and ensuring consistent development workflows for services across multiple deployment environments (Development, Staging, Production). Focuses on architectural rules, shared settings, and environment-specific deployment context.

This guide outlines critical reliability patterns for integrating advanced AI coding assistants into professional development workflows. It emphasizes best practices such as mandatory Git checkpointing, utilizing dedicated feature branches, breaking large tasks into incremental steps, and implementing comprehensive validation gates (linting, testing). Use this when developing fault-tolerant, AI-assisted applications to prevent accidental code breaks and maintain project stability.

This skill is intended to analyze and improve the quality of codebases, ensuring adherence to best practices and coding standards. Note: This specific file is a translation placeholder, and the core functionality description should refer to the original skill file for details.

This skill provides a comprehensive guide for creating production-quality custom Semgrep rules. It teaches best practices for detecting security vulnerabilities, enforcing robust coding standards, and identifying specific bug patterns. By emphasizing a test-first approach and utilizing advanced techniques like taint mode, users can write highly accurate static analysis rules that drastically reduce false positives.

This comprehensive guide covers essential security patterns for Perl development, addressing common vulnerabilities like SQL Injection, XSS, Path Traversal, and Shell Injection. It details best practices including using Perl's Taint Mode, implementing strict allow-list validation, performing safe file operations, and executing external commands securely to ensure robust and resilient applications.

This skill provides methods for reliably extracting typed, validated, and structured data from Large Language Models (LLMs), moving beyond simple text parsing. It covers best practices across major APIs (OpenAI's response_format, Anthropic's tool_use, Google's responseSchema) and local models. Key workflows include defining schemas (Pydantic/Zod), implementing constrained decoding, and building robust retry loops for production-grade data pipelines.

This skill provides a systematic cryptographic audit tool designed to review applications for security vulnerabilities. It scans source code and configuration files to detect weak hashing algorithms (MD5, SHA-1), insecure cipher modes (ECB), hardcoded secrets, and deprecated protocols like TLS 1.0. Essential for security assessments, compliance checks, and maintaining secure coding practices.

A comprehensive guide detailing best practices for executing commands on Windows using PowerShell and CMD. It addresses critical pitfalls such as handling spaces in file paths, ensuring correct character encoding (UTF-8), using native cmdlets, and managing long path limits. Essential for developers building robust, cross-platform Windows automation scripts.

This comprehensive guide covers idiomatic C# and modern .NET best practices for building robust, high-performance, and maintainable applications. Topics include immutability, dependency injection, explicit coding, proper async/await usage, the Options pattern, and the Result pattern. Essential reading for developers designing services with ASP.NET Core.

A comprehensive guide to idiomatic Go programming style and code clarity. This skill addresses best practices for line breaking, variable declaration intent, control flow structure (e.g., early returns, switch usage), and function design principles. Use it when writing, reviewing, or establishing project-wide coding standards to ensure maximum readability and maintainability.

This skill guides developers in writing robust and defensive Go code. It addresses common pitfalls that lead to runtime panics and silent data corruption, such as nil map writes, slice backing array aliasing, silent numeric truncation (int64 to int32), and inaccurate float comparisons. Use this when designing highly reliable Go systems that must withstand typical programmer errors and maintain data integrity.

A comprehensive skill for performing deep security audits and writing secure code in Go. It guides developers through identifying vulnerabilities like SQL injection, XSS, path traversal, and crypto misuse. The framework incorporates advanced techniques such as STRIDE/DREAD threat modeling, data flow tracing, and multi-stage review modes (Audit, Review, Coding), ensuring defense in depth for robust Go applications.