Skill UI

This skill guides developers and SaaS founders on minimizing operational costs when building on the Shopify platform. It covers deep dives into Shopify store plan rate limits, optimizing GraphQL and REST API usage, implementing robust cost tracking mechanisms, and applying advanced strategies like caching and bulk operations to reduce billable expenditures.

This guide provides a comprehensive framework for load testing Shopify app integrations, specifically designed to respect strict API rate limits. It teaches users how to plan and benchmark system capacity for high-traffic events like Black Friday/Cyber Monday (BFCM) or flash sales using tools like k6. Users learn to optimize for burst events, analyze GraphQL cost, and configure infrastructure scaling for reliable e-commerce performance.

This skill guides a systematic process for debugging reported issues. It explores the codebase to identify the root cause, traces the code path, and then generates a comprehensive GitHub issue. The fix plan strictly follows the Test-Driven Development (TDD) Red-Green cycle, ensuring proposed solutions are robust and durable, surviving major refactors.

A comprehensive guide to optimizing Webflow usage costs. This skill teaches advanced strategies for reducing API expenses by prioritizing CDN-cached reads (free and unlimited), implementing bulk endpoint operations, caching collection schemas, and replacing inefficient polling with Webhook-driven updates. It also provides methods for API usage monitoring and recommending the optimal site plan.

This skill generates complete, publication-ready, and SEO-optimized blog posts for WordPress. It enforces professional structure, factual rigor, and comprehensive SEO elements like Yoast metadata and JSON-LD schema, along with image SEO planning. It is ideal for content strategists and copywriters needing high-quality, engaging, and searchable articles.

This skill generates detailed implementation plans for multi-step tasks based on specifications before coding begins. It defines file structures, task granularity, and step-by-step instructions (TDD approach) to ensure clarity and testability. It includes self-check mechanisms and execution handoff options for AI agents or developers.

This skill executes implementation plans by assigning isolated sub-agents to each independent task. It ensures high quality through task-specific reviews and a final broad review. The workflow emphasizes continuous execution without unnecessary pauses, autonomous decision-making for conflicts, and isolated contexts to prevent contamination. Suitable for structured development plans where tasks can be decomposed.

This comprehensive guide serves as a decision flowchart for developers using Claude Code. It details when to use specific slash commands (/plan, /compact, /loop), select specialized agents (planner, code-reviewer, build-error-resolver), or invoke workflow skills (e2e-testing, tdd-workflow). It helps users select the optimal tool combination for complex tasks across the entire software development lifecycle, including feature planning, bug fixing, testing, and architectural design.

Design and plan end-to-end Azure IoT and Smart City solutions: gather requirements, define architecture, security, operations, cost, and phased delivery roadmap with concrete implementation artifacts.

This skill generates a complete, standalone, and highly structured pricing page in standalone HTML. It automatically respects the active design system (colors, typography, components) and supports defining 2-4 plan tiers, including feature cards, comprehensive comparison tables, and an FAQ section. Ideal for product marketing and sales-focused websites.

Squirrel is an advanced, full-cycle AI coding skill designed to guide software development from concept to production. It automatically detects the current project state (greenfield, in-progress, or mature) and adapts an 8-phase engineering pipeline. This comprehensive workflow covers planning, building, rigorous testing, bug hunting, code polishing, documentation, and deployment readiness, ensuring high-quality, maintainable results.

This skill assesses the AI readiness of a codebase by running a comprehensive audit against multiple technical and governance pillars. It generates a self-contained, detailed HTML dashboard that provides an overall maturity score, identifies strengths, and, most importantly, delivers a prioritized remediation plan (Fix First / Fix Next). Ideal for auditing repositories before major AI feature development.