Skill UI

This skill integrates advanced AI assistance into Git workflows within the Windsurf IDE. It automates complex source control tasks, including generating descriptive commit messages from staged changes, suggesting optimal branch names, assisting with merge conflict resolution, and streamlining common Git operations. Ideal for developers managing version control or needing robust support for collaborative coding environments.

This guide outlines common anti-patterns and critical mistakes when using the Windsurf AI IDE. It covers best practices for prompt engineering, managing workspace scope (especially in monorepos), distinguishing between Supercomplete and Cascade usage, and ensuring safe, maintainable AI-assisted coding workflows. Essential for new developers and team auditors.

This skill provides comprehensive, AI-assisted linting configuration for ensuring high code quality standards. It assists with setting up and integrating major linting tools (such as ESLint, Prettier, and Stylelint), helping resolve complex configuration conflicts, suggesting best practices based on project patterns, and fully automating code quality enforcement across the development lifecycle. Use this when establishing or refining coding standards for a project.

This skill provides AI-assisted performance profiling within the Windsurf IDE. It analyzes collected profiling data to pinpoint performance bottlenecks, suggest specific optimizations, and predict the impact of code changes. Use it when optimizing application speed, refining complex algorithms, or general performance tuning in a coding environment.

This skill manages complex, large-scale refactoring operations that span hundreds or thousands of files. It provides phased execution with checkpoints, comprehensive rollback capabilities, and AI-assisted planning. Use it for codebase migrations, major architecture refactoring, or system-wide updates.

This guide outlines critical reliability patterns for integrating advanced AI coding assistants into professional development workflows. It emphasizes best practices such as mandatory Git checkpointing, utilizing dedicated feature branches, breaking large tasks into incremental steps, and implementing comprehensive validation gates (linting, testing). Use this when developing fault-tolerant, AI-assisted applications to prevent accidental code breaks and maintain project stability.

This skill provides AI-powered assistance for advanced terminal operations within development environments. It helps users execute complex commands, suggests completions, explains cryptic error messages, and generates optimized shell scripts. Use it when you need advanced shell scripting help, command suggestions, or debugging support in your command-line interface (CLI) workflow.

End-to-end Neuropixels recording analysis covering SpikeGLX/OpenEphys/NWB loading, preprocessing, motion correction, Kilosort4 sorting, quality metrics, Allen/IBL curation, and AI-assisted visualization for extracellular electrophysiology.

This model provides an engineering operational framework for teams that leverage AI agents to generate large volumes of code. It shifts the focus from simple syntax to process quality, robust architecture design, rigorous testing, and systematic risk control, ensuring the development of highly stable and reliable systems in AI-assisted environments.

A specialized scripting language for Makepad, enabling advanced dynamic UI generation, complex workflow automation, and rapid application prototyping. It supports asynchronous operations (HTTP requests, timers) and is designed for integrating sophisticated, AI-assisted logic into application workflows.

This skill provides sophisticated project estimation by adapting to human-only, hybrid, or agent-first development modes. It uses research-backed PERT statistics and confidence bands (P50, P75, P90) to forecast development timelines for tasks, backlogs, and capacity planning. It continuously calibrates estimates based on actual completion data, ensuring accuracy in AI-assisted and hybrid development environments.

A comprehensive, multi-stage workflow for enhancing and structuring raw footage using advanced AI tools. It covers the entire pipeline—from initial recording (Screen Studio) through AI planning (Claude/Codex), deterministic cutting (FFmpeg), compositing (Remotion), asset generation (ElevenLabs/fal.ai), and final human polish (Descript/CapCut). Designed for users creating vlogs, tutorials, or polished corporate videos.