Skill UI

Automatically checks application metrics such as load times, bundle sizes, and API responses against predefined performance budgets, surfacing regressions and preventing slippage before deployments—ideal for CI/CD workflows.

This guide details how to integrate Vast.ai's GPU provisioning capabilities into automated CI/CD pipelines, such as GitHub Actions. It enables developers to run GPU-accelerated tests, model benchmarks, and validations automatically. Key features include robust instance lifecycle management (provisioning, running, and cleanup) and advanced cost-control mechanisms (e.g., setting budget limits) to ensure reliable and efficient testing in a cloud environment.

This guide establishes a fast, reproducible local development workflow for GPU workloads using Vast.ai. It covers key practices such as testing Docker images locally (in CPU mode), mocking external APIs like Vast.ai, and implementing robust unit and integration tests. This is essential for minimizing cloud GPU costs and accelerating the iteration cycle for complex AI/ML projects.

This comprehensive guide outlines best practices for optimizing vector indexes for production systems. It covers critical techniques such as tuning HNSW parameters, implementing quantization strategies, and optimizing memory usage. Use this when you need to balance search latency, recall, and scalability for large-scale vector databases.

A comprehensive guide to building and deploying Vercel Edge Functions. These functions run on Vercel's global Edge Network (V8 isolates), providing ultra-low latency and zero cold starts. Learn how to use Web Standard APIs for critical tasks such as authentication, geolocation routing, A/B testing, and high-performance API middleware, drastically improving application speed and user experience.

This comprehensive workflow guides users through a multi-phase process for assessing web application security. It is designed to systematically test for common vulnerabilities listed in the OWASP Top 10, including SQL injection, XSS, broken authentication, and access control issues. Ideal for professional penetration testing, security auditing, and bug bounty hunting.

This skill automatically generates structured and user-friendly changelogs by analyzing the complete git commit history. It groups commits by time period (daily/weekly) and classifies changes into key categories (Features, Fixes, Docs, etc.), providing a concise summary of recent development activity for end-users. Ideal for answering 'what changed recently' or summarizing project updates.

Automatically generates two complementary onboarding documents for any codebase: a Principal-level guide focusing on design philosophy, technical debt, and architectural 'why'; and a Zero-to-Hero guide providing step-by-step setup, development workflows, and practical 'how-to' instructions. Ideal for new team members or documenting complex systems.

This skill transforms generated wiki Markdown files into a polished, professional VitePress static documentation site. It automatically integrates a dark theme, enhances interactivity, and supports complex Mermaid diagrams with careful CSS and JavaScript fixes. Use this when the goal is to build a fully browsable, deployed documentation website from raw wiki content.

This skill leverages AI to analyze your application and automatically generate highly optimized Dockerfiles. It incorporates industry best practices like multi-stage builds, minimal base images, and robust security configurations. Use it when containerizing applications or needing to optimize existing Docker configurations for production deployment and efficient orchestration.

This skill automates the entire software release workflow within Windsurf. It analyzes commit history based on conventional commits to determine the correct semantic version bump (major, minor, or patch). It then automatically generates comprehensive changelogs, manages Git tags, updates version files, and publishes the final release package to a registry. It is essential for teams implementing robust CI/CD practices.

This skill automates the creation of comprehensive test suites for any codebase. Utilizing advanced AI capabilities, it analyzes function signatures, automatically identifies potential edge cases, generates meaningful assertions, and produces necessary mock data and fixture files. It is essential for developers needing robust unit tests, increasing code coverage, and adopting Test-Driven Development (TDD) workflows across various frameworks like Jest or pytest.