Skill UI

This comprehensive guide details the credit-based usage model of the Windsurf AI platform. It explains how various powerful models (e.g., SWE-1, GPT-4o) consume credits and provides strategies for optimizing AI usage costs. Learn how to monitor remaining credits, understand different pricing tiers (Free, Pro, Teams), and implement prompt engineering techniques to maximize efficiency and prevent mid-session interruptions.

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.

A comprehensive guide to securing development workspaces using Windsurf. This skill teaches how to apply best practices for workspace isolation, prevent sensitive data (secrets, PII) from leaking into AI indexes, manage telemetry, and ensure compliance by configuring exclusion files and security rules.

This skill guides the development of custom extensions for the Windsurf environment, leveraging the full VS Code Extension API. You will learn to track various workspace events—such as file saves, editor changes, and terminal outputs—and integrate this data with external services by sending structured webhooks. This is essential for building complex workflow automation, implementing custom IDE features, or creating data analytics tools within the development lifecycle.

Guides writing Hookify rules that watch commands, files, prompts, or stop events, using YAML frontmatter to define patterns, actions, and messages for enforcing safety checks or reminders.

This guide outlines best practices for creating robust and optimized Zustand stores in TypeScript. It covers fundamental patterns, such as separating state and actions, utilizing `subscribeWithSelector` middleware, and implementing individual selectors to prevent unnecessary re-renders. Essential for building scalable, high-performance frontend applications with React.

Apify Actorization is a process that transforms existing, standalone software or scripts (like CLI tools) into standardized, reusable serverless applications called Actors. Actors are packaged as Docker images, accepting structured JSON inputs and producing structured JSON outputs. This skill guides developers on migrating projects to the Apify platform, ensuring compatibility, and enabling scalable, event-driven data processing pipelines.

This comprehensive guide helps users build, audit, and debug robust analytics tracking systems using GA4 and Google Tag Manager. It focuses on establishing a consistent event taxonomy and capturing every meaningful user action—from initial visits to complex conversions—ensuring data integrity for accurate decision-making.

This skill guides the user through a structured process of requirement clarification before any development work begins. It ensures that all key details—including objectives, scope, constraints, and acceptance criteria—are explicitly defined. It prevents costly rework by forcing a pause and systematically identifying 'must-have' missing information.

A comprehensive guide for designing and building scalable, resilient serverless applications and event-driven architectures on AWS. It covers best practices using Lambda, API Gateway, DynamoDB, Step Functions, and adheres to the AWS Well-Architected Framework principles, ensuring optimal performance, cost-efficiency, and maintainability.

This comprehensive skill guides users through the entire debugging lifecycle, from reproducing elusive bugs to tracing the root cause, implementing permanent fixes, and preventing future regressions. It covers advanced techniques like binary search, time travel debugging, and handling common patterns such as race conditions and null values, ensuring professional and systematic troubleshooting for any production issue.

Diagnose and fix failing or flaky Playwright tests via a systematic reproduce-trace-categorize-fix workflow, validate stability by repeated runs, and recommend CI safeguards to prevent regressions.