Skill UI

Flash Attention optimizer delivers 2-4x speedup and 10-20x memory savings for transformer attention, ideal when training or running long-context models that hit GPU memory or latency limits; supports PyTorch native scaled_dot_product_attention, the flash-attn library, H100 FP8 precision, and sliding-window attention.

Expert in designing and implementing advanced Retrieval-Augmented Generation (RAG) pipelines. This role focuses on optimizing the entire information retrieval process—from document chunking and embedding model selection to vector database architectures and hybrid search strategies. The goal is to bridge the gap between raw knowledge documents and accurate LLM understanding, drastically reducing hallucination and enhancing context relevance for enterprise applications.

Automates React Context setup within frontend development, guiding users through best practices, production-ready code, and validation for React-related modern web patterns.

This skill specializes in transforming theoretical threat models, risk assessments, and business context into concrete, actionable security requirements. It is essential for writing detailed security user stories, defining robust acceptance criteria, building comprehensive security test cases, and ensuring compliance requirement mapping. Use it when bridging the gap between identifying a vulnerability and specifying how the system must be secured.

Vexor is a powerful command-line interface designed for advanced semantic search across local files. By utilizing vector embeddings and integrating with large language models (like Claude/Codex), it allows users to search files based on meaning and context, rather than just exact keywords. This is ideal for large codebases or document repositories where traditional keyword search methods are insufficient.

This skill manages the integration of Model Context Protocol (MCP) servers with Windsurf, significantly extending its operational capabilities. It enables Windsurf to interact with external resources, including databases, file systems, APIs, and custom tools through a standardized protocol. Use this when configuring or utilizing advanced, external tool integrations within the Windsurf environment.

A comprehensive guide to establishing production-ready coding standards and context for the Windsurf AI environment. Learn how to utilize root-level rules (.windsurfrules), granular workspace rules, Model Context Protocol (MCP) server integration, and advanced prompt engineering to guide the AI and maintain consistent code quality across projects.

Expert skill for building modern, production-ready Chrome Extensions using Manifest V3 standards. Covers advanced topics including service worker management, content script injection, secure cross-context communication (message passing), and implementing best practices like `declarativeNetRequest` and secure storage APIs.

A powerful tool to scaffold and ship production-ready Model Context Protocol (MCP) servers directly from OpenAPI specifications. It supports Python and TypeScript, ensuring schema validation, safe evolution, and robust tool definition generation, eliminating the need for manual wrapper coding. Use it to expose existing REST APIs to LLM agents or build shared tool integrations.

Explains the altitude-and-horizon mental model that differentiates PM and Director thinking, helping leaders diagnose friction zones, create cascading context, and focus on system-level strategy when scope or direction is unclear.

This skill provides comprehensive techniques for optimizing prompts used with any Large Language Model (LLM). It teaches proven methodologies—including Role definition (R), Context setting (S), Constraints (C), Instructions (I), and Templates (T)—to transform vague inputs into precision-engineered instructions. Users can reliably achieve structured JSON output, implement Chain-of-Thought reasoning, reduce hallucinations, and minimize token usage, ensuring consistent and high-quality results across different AI platforms.

This skill establishes a rigorous framework for building deep architectural context by performing ultra-granular, line-by-line analysis of code. It applies methodologies like First Principles and 5 Whys to maintain a stable, evolving mental model of the entire system, making it essential for pre-vulnerability security auditing, threat modeling, and complex architecture reviews.