Skill UI

Intelligently executes git commit by adhering to the Conventional Commits specification. The tool analyzes the staged or working directory diff to automatically detect the change type (e.g., feat, fix, docs), the affected scope, and generates a standardized, semantic commit message. This ensures your project history remains clean, readable, and compliant with best development practices. Ideal for maintaining robust version control.

Automates repository, issue, PR, branch, and CI/CD operations through Rube MCP’s GitHub toolkit, enabling teams to programmatically manage workflows, reviews, searches, and deployments once the MCP and GitHub connections are active.

Guides teams through creating a complete GitHub Copilot configuration by outlining required instructions, reusable skills, and agent/workflow files tailored to the chosen tech stack and workflow preferences.

Transforms unstructured and messy bug reports—including pasted error logs, voice dictations, and screenshots—into clean, actionable, and highly structured GitHub Issues. It automatically populates key sections like reproduction steps, expected/actual behavior, impact severity, and environment details, ensuring developers receive comprehensive and ready-to-use information.

Creates a production-ready Model Context Protocol server in Go by scaffolding modules, tools, resources, configuration, README guidance, and basic tests built around the official GitHub SDK for rapid setup.

Bulk migrate repo labels and Project V2 metadata into GitHub org issue fields, converting label-based tags into typed fields, optionally removing old labels, and syncing project field values for cleaner structured issue tracking.

A comprehensive meta-skill template designed for developers to scaffold, structure, and define specialized Agent Skills for AI platforms like GitHub Copilot. It guides users through mandatory requirements, including folder naming conventions, YAML frontmatter best practices (name, description), and structuring the skill body with detailed workflows and documentation sections. Use this when building complex, specialized AI capabilities.

Reads `.agent.md` or `.prompt.md` files, assesses task complexity, tooling, and requirements, then recommends the most cost-efficient GitHub Copilot model(s) (e.g., GPT-5, Claude Sonnet) with rationale for users across different subscription tiers and priorities.

This tool searches the current GitHub repository and retrieves all issues explicitly assigned to the user. It goes beyond simple listing by analyzing key issue metadata—such as age, comment volume, and current status (open/closed)—to proactively suggest which issues require immediate attention or focus. It is indispensable for contributors, project managers, or developers who need a quick, prioritized overview of their assigned workload.

This skill provides advanced architectural guidelines for generating premium, award-level web experiences. It guides code generation beyond basic HTML/CSS, focusing on creating immersive digital environments. Key areas include sophisticated motion design (scroll-driven narratives, micro-interactions), establishing strong visual identities (e.g., Brutalism, Glassmorphism), and enforcing strict performance best practices like hardware acceleration and accessibility compliance.

This tool acts as an expert prompt engineer, guiding users through a systematic discovery process to create highly structured, production-ready prompts for AI assistants like GitHub Copilot. It covers defining persona, specifying complex tasks, managing context variables, integrating tools, and enforcing strict output standards, ensuring the resulting prompt is comprehensive and actionable for advanced AI agents.

Automates converting PPTX, PDF, HTML, or Google Slides inputs into a GitHub Pages repo, covering conversion, asset handling, repo creation, and returning the live URL so presentations or HTML content can be shared quickly.