moai-alfred-language-detection
Auto-detects project language and framework from package.json, pyproject.toml, Cargo.toml, go.mod, and other configuration files with comprehensive pattern matching based on 17,253+ production code examples.
Auto-detects project language and framework from package.json, pyproject.toml, Cargo.toml, go.mod, and other configuration files with comprehensive pattern matching based on 17,253+ production code examples.
Tenzir Python coding standards and tooling setup. Use when writing python code, running ruff/mypy/pytest, encountering pyproject.toml/uv.lock, or setting up a new Python project.
Enables ultra-granular, line-by-line code analysis to build deep architectural context before vulnerability or bug finding.
Perform code reviews using OpenAI Codex CLI to identify bugs, security vulnerabilities, performance issues, and code quality problems. Use when the user asks to review code, check for issues, security audit, or before committing. Requires Codex CLI installed.
Rev - Senior Full-Stack Code Reviewer with 12+ years experience in Java/Kotlin and TypeScript/React. Use when reviewing code quality, checking security vulnerabilities, validating style compliance, running static analysis tools, or ensuring test coverage. Also responds to 'Rev' or /rev command.
Reviews code for quality, security, and best practices. Use proactively after code changes.
Systematic project orientation for unfamiliar codebases. Automatically activates when Claude detects uncertainty about project state, structure, or tooling. Analyzes git state (branch, changes, commits), project type (language, framework, structure), and development tooling (build, test, lint, CI/CD). Provides structured summary with risk flags and recommendations. Use when entering new projects or when working on shaky assumptions.
Guide for creating IntelliJ Platform plugins using Gradle and Kotlin/Java. Use when users want to create, configure, or develop plugins for IntelliJ IDEA or other JetBrains IDEs.
Systematic code review guidance covering correctness, maintainability, security, and performance. Activates for PR reviews and code quality checks.
Enterprise systematic code review orchestrator with TRUST 5 principles, multi-language support, Context7 integration, AI-powered quality checks, SOLID principle validation, security vulnerability detection, and maintainability analysis across 25+ programming languages; activates for code reviews, quality standard validation, TRUST 5 enforcement, architectural audits, and automated review automation
Expert code review specialist. Reviews for quality and intent alignment. Use immediately after writing or modifying code, or when user requests code review. Handles both uncommitted changes and targeted file reviews.
Code hygiene, quality gates, and pre-commit workflows. Use for linting, type checking, testing, and fixing errors.
Analyzes project structure, technology stack, patterns, and conventions. Use when starting development tasks, reviewing code, or understanding an existing codebase.
Roast a repository to identify issues, then translate to constructive feedback. Use when user wants code review, wants to find problems, asks to "roast" their code, or wants honest feedback about their codebase.
Navigate, analyze, and modify codebases using LSP semantic navigation. Use when user needs code refactoring, bug fixing, feature implementation, code analysis. Returns structured code changes with LSP navigation metadata.
Guide for simplifying and refining code after coding sessions. Use when cleaning up complex code, reviewing PRs for readability, or applying consistent refactoring patterns.
Evaluate external PR suggestions (Gemini, CodeRabbit) against project conventions. Use when asked to review or agree with external code review comments.
Formats and styles content for professional GitHub presentation. Use when the user asks to style files for GitHub, format documentation, improve markdown presentation, or prepare repository for publishing. Applies clean, consistent GitHub-flavored markdown.
Unified linting and auto-fix for Python (Ruff) and TypeScript (ESLint) in monorepo. Use when fixing lint errors, running pre-commit checks, or diagnosing persistent code quality issues. Orchestrates auto-fix first, then root-cause analysis.
This skill should be used when the user asks to "review code", "perform code review", "check code quality", "review PR", "provide code feedback", or needs guidance on code review best practices and standards in k2-dev workflows.
Establish clear and maintainable comments throughout JavaScript modules, CSS, and HTML files in this static website project. Use this skill when adding, updating, or reviewing comments in source code to ensure they follow consistent conventions and improve code readability.
Extract and generate coding best practices from PR review comments. Use when the user asks to "extract best practices", "analyze PR comments", "generate coding standards", "create best practices from PRs", or "update coding guidelines from reviews".