Skill UI

This guide outlines comprehensive best practices for documenting Java code using Javadoc comments. It covers how to properly document public, protected, package-private, and private members, along with the correct usage of various tags like @param, @return, @throws, @see, and specialized syntax for code snippets and versioning. Following these standards ensures API documentation is accurate, maintainable, and adheres to professional Java development norms.

A comprehensive automation toolkit for Mixpanel product analytics, accessible via Rube MCP. Automate key data tasks including event aggregation, detailed segmentation, conversion funnel analysis, user profile management, cohort tracking, and running custom JQL queries. Ideal for data analysts and product managers needing to deeply analyze user behavior patterns.

This skill provides an interactive, guided onboarding tour for the Context-Matic MCP server. It addresses the challenge of general AI models relying on outdated or incorrect public code by acting as a live, version-aware grounding layer. The tour walks users through the server's core function, demonstrates key tools (like fetching APIs, searching models, and finding endpoints), and guides them through selecting and exploring available APIs for their specific project language.

A comprehensive matrix detailing minimum required dependency versions for stable operation with React 18.3.1 and React 19.0.0. Use this guide before running `npm install` during major React upgrades to check for peer dependency conflicts, assess compatibility risks (e.g., concurrent mode issues), and determine if a package needs version pinning or specific migration strategies.

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.

Generates high-converting, SEO-optimized content for competitor comparison and alternative pages. This tool creates structured content for 'X vs Y' layouts, 'Alternatives to X' roundups, and feature matrices, ensuring comprehensive coverage for competitive intent keywords. It includes advanced SEO elements like Schema Markup and strategic CTA placement to maximize conversion rates and search engine ranking.

This skill provides comprehensive commands for creating, managing, versioning, and querying structured datasets within the Arize platform. It covers dataset CRUD operations, appending examples, and exporting data in various formats (JSON, CSV, Parquet) using the `ax` CLI. Ideal for preparing test data, generating evaluation examples, or retrieving golden datasets for LLM development and model testing.

Generates a copilot-instructions blueprint tailored to each repository by analyzing existing code patterns, versions, and architectural standards so GitHub Copilot stays aligned with project guidelines.

Automates the creation of GitHub issues by parsing an implementation plan, verifying existing issues, and generating one issue per phase using feature or chore templates with structured titles and requirements.

This comprehensive guide details how to configure and manage GitHub Dependabot. It covers everything from setting up initial dependency updates (npm, pip, docker, etc.) to advanced strategies like monorepo glob patterns, cross-directory grouping, and multi-ecosystem updates. Learn how to automate dependency vulnerability detection and version upgrades efficiently.

FAF Expert is an advanced tool for creating standardized, persistent context for complex software projects. It uses the IANA-registered FAF format to transform codebases into AI-intelligent assets. Use it for multi-AI workflow management (Claude, Gemini, etc.), enterprise-grade deployment, and standardizing project context across development lifecycles.

Automatically scans any codebase, detects its stack, and generates a persistent project.faf AI context plus readiness scoring so every AI tool can instantly understand and contribute to your project.