Skill UI

This skill activates the P7 Senior Engineer mode, designed for rigorous, solution-driven execution under P8 supervision. It is used when the user explicitly requests 'P7模式' or when invoked as a sub-task executor by P8. The process involves three key stages: designing a detailed implementation plan and impact analysis, executing the core coding, and finally, completing a mandatory three-question self-review, ensuring high quality and comprehensive verification.

This CLI alias implements the PUA Loop protocol, designed for running structured, iterative verification cycles. It helps developers set up and manage complex coding tasks that require explicit verification commands and defined stop conditions. It serves as a powerful wrapper for AI coding assistants like Codex/Claude, ensuring robust and traceable development workflows.

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.

Generates agent-friendly DESIGN.md for Google Stitch, encoding strict typography, color, layout, component, and motion rules to produce premium non-generic UI screens.

Behavioral guidelines for writing, reviewing, and refactoring code with LLMs, emphasizing minimalism, clear assumptions, surgical edits, and verifiable success criteria to avoid common machine-assisted coding mistakes.

This prompt guides software engineers to create comprehensive technical implementation plans for new features. It covers system architecture, database design, API specifications, frontend structure, and security considerations within a monorepo environment. Ideal for planning SaaS features before coding begins.

A comprehensive methodology guiding technical professionals through the design process before coding. It helps structure complex features by producing detailed design documents, including system overviews, data models, API specifications, multiple trade-off analyses, and implementation plans, ensuring robustness and clarity from the start.

This comprehensive guide outlines best practices for writing high-quality, scalable, and maintainable code in .NET/C#. It covers core architectural principles, including SOLID, dependency injection, and design patterns (e.g., Command Handler). Furthermore, it addresses modern challenges such as structured logging, async/await patterns, secure coding, robust testing standards, and advanced AI integration using Semantic Kernel.

This expert system generates a comprehensive and best-practice-oriented .editorconfig file. It analyzes the project structure and user preferences to enforce coding style consistency (e.g., spaces vs. tabs, indentation size, line endings, trailing whitespace) across diverse IDEs and text editors. Essential for maintaining clean, standardized code across development teams and version control systems.

This comprehensive guide provides a detailed framework for authoring effective and structured SKILL.md files for AI coding agents. It covers best practices for structuring content, including frontmatter fields, defining natural language triggers, establishing core principles, and incorporating advanced elements like decision trees and verification checklists, ensuring agents receive clear, actionable, and consistent technical guidance.

Transforms existing code files into highly effective learning resources by adding context-aware educational comments. Acting as an expert educator, this tool tailors explanations—from foundational concepts for beginners to deep architectural insights for advanced practitioners—while strictly maintaining the original file's structure, encoding, and syntax. Ideal for generating self-documenting, pedagogically rich codebases.

This guide outlines the structure and content guidelines for an AGENTS.md file. This file serves as a comprehensive 'README for agents,' providing detailed, technical context and operational instructions (such as setup, development workflow, testing procedures, and code style) that enable advanced AI coding agents to interact with and understand a codebase effectively. It greatly complements traditional READMEs by focusing purely on machine-readable technical requirements.