Skill UI

Provides copywriters with clear, structured guidance for crafting persuasive marketing copy across home, landing, pricing, feature, and product pages, emphasizing clarity, benefits, customer language, and proven CTA formulas.

This framework provides a systematic guide for evaluating and improving user interface usability based on established heuristic principles. It covers core concepts like 'Don't Make Me Think' and 'Get Rid of Half the Words,' helping users conduct detailed usability audits, analyze navigation flow, and optimize copy. Use this when reviewing a product's user experience, addressing user confusion, or performing a formal UX review to enhance clarity and efficiency.

Audit and optimize content for AI search engines and generative AI overviews. Focus on citability, entity clarity, brand signals, and technical accessibility to improve visibility in AI-generated answers and search results. Includes analysis of crawler access and brand mentions.

This skill explains complex concepts using the Socratic method. Instead of delivering direct answers or textbook definitions, it engages the user in a reflective, conversational dialogue. By guiding the user through thought experiments, small observations, and simple analogies, the assistant helps the user construct understanding step-by-step, facilitating deeper clarity through active reasoning. Ideal for understanding theories, abstract ideas, or system mechanics.

Provide step-by-step explanations of specific files, functions, or modules, leveraging the understand-explain workflow to map graph context, layer placement, internal structure, and data flow for developers needing deep clarity.

This skill reviews code differences (diffs) to identify opportunities for improvement in clarity, reusability, efficiency, and overall quality. It employs multiple specialized sub-agents (e.g., Code Reuse, Efficiency, Quality) to audit changes. It can provide high-confidence, behavior-preserving fixes when requested, ensuring the code adheres to best practices without introducing regressions. Best used when refactoring, cleaning up, or auditing a specific code scope.

An AI communication style that minimizes token usage while maintaining technical accuracy. It removes filler words, articles, and hedging, adhering to Simplified Technical English principles. Offers intensity levels from lite to ultra and classical Chinese variants for maximum brevity and clarity in technical contexts.

Guides AI agents through analyzing working code, spotting overly complex structures, then refactoring for clarity while preserving exact behavior and project conventions, especially after reviews or high-pressure edits.

This skill involves recording technical decisions and documentation within software projects. It focuses on capturing the reasoning behind design choices, architecture decisions (ADRs), and public API changes. It helps future engineers and agents understand the codebase context, constraints, and trade-offs. It includes guidelines for writing ADRs, inline comments, and API documentation to maintain clarity and maintainability.

A comprehensive guide to idiomatic Go programming style and code clarity. This skill addresses best practices for line breaking, variable declaration intent, control flow structure (e.g., early returns, switch usage), and function design principles. Use it when writing, reviewing, or establishing project-wide coding standards to ensure maximum readability and maintainability.

This skill helps refine vague, raw ideas into sharp, actionable concepts. It guides users through structured divergent thinking (expanding options, generating variations) and convergent thinking (stress-testing assumptions, clustering directions). The process culminates in a detailed one-pager including Problem Statements, MVP Scope, and key assumptions to validate, ensuring focus and clarity before development.

This skill involves creating structured specifications before writing any code to serve as a shared source of truth between developers and engineers. It is used when starting new projects, features, or significant changes where requirements are unclear or ambiguous. The workflow includes a scope check, specifying objectives, planning, task breakdown, and implementation with human reviews at each phase. It helps decompose complex requirements into capability maps and ensures clarity before coding begins.