Skill UI

Master the art of developing robust and scalable Python applications that interface with Microsoft Dataverse. This skill covers implementing enterprise-grade best practices, including comprehensive error handling using DataverseError hierarchy, advanced retry logic with exponential backoff, and optimizing API calls using OData standards (filtering, selecting, and expanding). It ensures code is clean, maintainable, and production-ready.

Expert skill for generating production-quality Python scripts specifically for the FreeCAD CAD application. This includes automating complex 3D modeling tasks, creating parametric FeaturePython objects, performing advanced geometric operations (Boolean, Fillet, Loft), building custom GUI tools using PySide, and handling mesh/FEM analyses via the FreeCAD Python API. Ideal for CAD automation and engineering visualization.

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.

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.

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.

Provides patterns for migrating test files to React 19 compatibility, covering act() imports, Simulate removal, StrictMode call count changes, and cleanup of react-dom/test-utils. Helps developers update testing codebases efficiently.

This skill generates a detailed, multi-phase plan for complex, multi-file refactoring projects. It ensures safety by first analyzing the codebase, identifying dependencies, and structuring changes in a safe sequence (e.g., Types first, then implementations, followed by tests and cleanup). It forces the AI to output a comprehensive plan, including rollback steps and verification points, and waits for user confirmation before making any actual code changes.

Acts as a senior software engineer to meticulously review and refactor entire codebases. This skill ensures that the code is clean, highly maintainable, and strictly adheres to defined coding standards and best practices specified across multiple project instruction files. It guarantees the integrity of the existing file structure and ensures all unit tests remain passing after modifications.

This skill guides developers to finalize a development branch after testing passes. It involves verifying tests, detecting the git environment, presenting integration options (merge, PR, keep), executing the chosen action, and cleaning up worktrees. It ensures safe integration and prevents accidental data loss during branch management.

This skill guides the setup of isolated development environments using Git worktrees and best practices. It ensures that all development work is kept separate from the main repository branch, preventing accidental commits or state corruption. The process involves checking the current worktree status, creating new isolated environments (prioritizing native tools), installing project dependencies (e.g., Node, Python, Go), and running essential baseline tests to guarantee a clean, stable starting state.

A comprehensive skill for creating technical and scientific documentation using Markdown as the source format, enhanced by embedded Mermaid diagrams. This method establishes text-based diagrams as the canonical standard, ensuring that all visualizations are clean, editable, and highly readable in version control systems like Git. It is ideal for generating reports, architectural diagrams, workflows, and any content that requires cross-platform rendering and version history.

Process, clean, compare, and search tandem mass spectra with matchms 0.33.1. Covers MS/MS file I/O, metadata harmonization, peak filtering, spectral similarity scoring, library matching, score matrices, and molecular-similarity networks in Python.