Skill UI

A comprehensive three-column layout template designed for high-readability technical documentation, such as API references, tutorials, and guides. It features a sticky side navigation, main article body with support for code blocks and callouts, and a scroll-spy Table of Contents (TOC). Includes search and version control.

This guide provides a comprehensive reference on Agent Skills, a standardized and powerful method for providing structured context, workflows, and tools to Large Language Models (LLMs). It details the anatomy of the SKILL.md file, the three-stage progressive disclosure loading process, and best practices for creating both capability (tool-based) and process (workflow-based) primitives. Use this resource when designing, reviewing, or debugging agent-driven applications to ensure reliable and context-efficient performance.

This skill is designed to mitigate false-positive safety triggers from strict AI classifiers (e.g., cyber, bio/chem, reasoning). It operates by making minimal, surgical edits to sensitive phrases, abstracting away specific domains or actions while preserving the original benign intent and structure. It ensures the prompt remains policy-compliant without losing its core purpose, making it ideal for academic or defensive inquiries.

WGM is a robust, agentic methodology designed to transform vague or rough requirements into working, validated software. It enforces a disciplined workflow across six stages: deep alignment (Grill), structured planning, deterministic iterative building (Loop), mandatory holdout-scenario judging, and final documentation audits. It ensures that the resulting code converges against rigorously tested acceptance criteria rather than relying on single-pass generation.

Design a persistent multi-agent operating system on Claude Code with kernel routing, specialist agents, slash commands, file-based memory, and scheduled automation for long-lived projects.

This model provides an engineering operational framework for teams that leverage AI agents to generate large volumes of code. It shifts the focus from simple syntax to process quality, robust architecture design, rigorous testing, and systematic risk control, ensuring the development of highly stable and reliable systems in AI-assisted environments.

A comprehensive guide to implementing Clean Architecture patterns for both Android and Kotlin Multiplatform (KMP) projects. It covers robust module structuring, dependency inversion rules, defining UseCases and Repositories, and designing the data layer using technologies like Room, SQLDelight, and Ktor. Learn how to separate concerns, maintain platform independence, and manage complex data flows.

This guide outlines how to build new API connectors or providers that strictly adhere to the existing integration architecture and patterns of a target repository. It is designed for adding integrations while maintaining architectural consistency (e.g., layout, configuration schema, authentication model, and testing style), preventing the creation of novel, unsupported patterns.

This comprehensive guide outlines industry best practices for designing robust and consistent REST APIs. It covers proper resource naming conventions, standardized HTTP method semantics, detailed HTTP status codes (e.g., 201, 404, 422), structured response formats (including pagination and links), and advanced strategies like cursor-based pagination. Essential for building scalable and maintainable APIs.

A comprehensive guide covering scalable backend architecture patterns, including Repository, Service, and Middleware design. It details best practices for building robust APIs using Node.js, Express, and Next.js. Topics covered include RESTful API structuring, database query optimization (preventing N+1 issues), implementing database transactions, and integrating caching strategies like Redis. This guide is essential for developing high-performance, maintainable server-side applications.

A comprehensive, implementation-ready guideline for creating a modern, editorial design system tailored for books, magazines, and reports. This skill defines foundational constraints, including typography scales, color tokens, spacing rhythm, and accessibility standards (WCAG 2.2 AA), ensuring visual consistency across all digital and print media.

Code Health MCP provides structural maintainability feedback and design-level health scores, going beyond standard linting. It is crucial for AI-assisted coding workflows, allowing users to review code quality, verify score deltas after changes, and gate commits or pull requests to prevent codebase regression. Use it when refactoring, updating legacy modules, or ensuring the integrity of large diffs.