Skill UI

This tool generates highly standardized and ultra-compressed commit messages following the Conventional Commits specification. It ensures that commits are concise, professional, and adhere to strict formats (e.g., type(scope): summary). It intelligently generates a body only when the context (like breaking changes or complex reasoning) requires it, significantly reducing noise and maintaining a clean, clear project history.

This workflow guides developers through generating standardized, descriptive commit messages using the Conventional Commits specification. It provides a structured XML template (including type, scope, description, body, and footer) and integrates directly into the Git workflow, ensuring project history is clean, traceable, and machine-readable. Ideal for maintaining large, collaborative codebases.

This skill performs a comprehensive security audit of Model Context Protocol (MCP) server configurations found in .mcp.json files. It is designed to identify critical vulnerabilities, including hardcoded secrets (API keys, tokens), dangerous shell injection patterns, unpinned dependencies, and compliance issues regarding approved server lists. Use this skill during security reviews, project onboarding, or pre-commit checks to ensure secure deployment.

A powerful tool that converts complex Unified Modeling Language (UML) diagrams—such as Sequence, Class, Activity, and State diagrams—into plain text ASCII art. This is crucial for documentation in environments that do not support image embedding, such as terminal sessions, README files, or Git commit messages. Supports both standard ASCII and enhanced Unicode ASCII formats for better visual fidelity.

Template for creating time-boxed technical spike documents that capture research questions, deliverables, success criteria, and decision rationale before committing to implementation.

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.

Defines mandatory contribution guidance for repository work, insisting contributors locate workflow documentation, follow branch/commit/PR templates, and run required linters or tests before submitting changes, without executing forbidden scripts.

Guides Python authors from commit to release with end-to-end steps for structuring src layouts, choosing setuptools/hatchling/flit/poetry backends, enforcing SOLID+type-hinting patterns, orchestrating lint/test/CI, managing PEP 440 semantics, and publishing trusted releases to PyPI.

Transforms repo structure and commit history into two actionable markdowns—an architecture summary and a narrative story—so analysts can trace system intent, data flow, and team evolution.

Ensures every framework-specific decision is traced to authoritative docs: detect stack versions, fetch relevant pages, implement documented patterns, cite sources, and flag conflicts before committing code.

Guides a project planning agent through researching, decomposing, and documenting multi-commit development plans before coding, enforcing autonomous research protocols and template-driven plan outputs for structured PR execution.

A comprehensive methodology for pinpointing the root cause of complex bugs, regressions, or unexpected behavior in large codebases. Techniques include binary search debugging, Git bisect for tracking regressions across commits, strategic data/control flow logging, component isolation, and advanced breakpoint strategies (conditional breakpoints, watch expressions). Ideal for scenarios where the bug source is unclear or difficult to reproduce.