Documentation

Analyze and optimize user prompts for clarity, specificity, and completeness using interactive questionnaires or direct analysis. Use this skill when user requests are vague, ambiguous, incomplete, or lack necessary details. Supports two modes - Interactive Mode (uses AskUserQuestion tool for guided clarification) and Direct Analysis Mode (provides optimization suggestions). Triggers on prompts containing vague language like "something", "thing", "stuff", "it", or when requests lack context, technical specifications, success criteria, or examples. When user requests interactive/questionnaire mode, use AskUserQuestion to guide them through structured questions. Helps transform unclear requests into well-structured, actionable prompts.

Progressive disclosure guide to TabzChrome capabilities. This skill should be used when users ask about profiles, terminal management, browser automation, MCP tools, audio/TTS notifications, integration, debugging, API, or setup. Provides on-demand help organized by topic with references to detailed documentation.

文档模板集合；创建Wiki或方案包文件时读取；包含所有知识库模板和方案文件模板

Write clear, engaging technical content from real experience. Use when writing blog posts, documentation, tutorials, or technical articles.

Documentation template collection; read when creating Wiki or solution package files; includes all knowledge base templates and solution file templates

Apply safe refactoring patterns to improve code structure without changing behavior. Use when cleaning up code, reducing technical debt, or improving maintainability.

Apply XP practices including pair programming, ensemble programming, continuous integration, and sustainable pace. Use when implementing agile development practices, improving team collaboration, or adopting technical excellence practices.

Unvarnished technical criticism combining Linus Torvalds' precision, Gordon Ramsay's standards, and James Bach's BS-detection. Use when code/tests need harsh reality checks, certification schemes smell fishy, or technical decisions lack rigor. No sugar-coating, just surgical truth about what's broken and why.

Comprehensive guide for PostgreSQL psql - the interactive terminal client for PostgreSQL. Use when connecting to PostgreSQL databases, executing queries, managing databases/tables, configuring connection options, formatting output, writing scripts, managing transactions, and using advanced psql features for database administration and development.

Searching internet for technical documentation using llms.txt standard, GitHub repositories via Repomix, and parallel exploration. Use when user needs: (1) Latest documentation for libraries/frameworks, (2) Documentation in llms.txt format, (3) GitHub repository analysis, (4) Documentation without direct llms.txt support, (5) Multiple documentation sources in parallel

Kessoku compile-time DI with parallel initialization for Go. Use when writing or debugging kessoku providers/injectors, enabling async dependencies, migrating from google/wire, or fixing go:generate/codegen issues in Go services.

Guide for implementing MongoDB - a document database platform with CRUD operations, aggregation pipelines, indexing, replication, sharding, search capabilities, and comprehensive security. Use when working with MongoDB databases, designing schemas, writing queries, optimizing performance, configuring deployments (Atlas/self-managed/Kubernetes), implementing security, or integrating with applications through 15+ official drivers. (project)

Guide for implementing Google Gemini API document processing - analyze PDFs with native vision to extract text, images, diagrams, charts, and tables. Use when processing documents, extracting structured data, summarizing PDFs, answering questions about document content, or converting documents to structured formats. (project)

Research topics by verifying actual source content. Use when asked to research or study links and documentation.

Write Python docstrings following the Google Python Style Guide, using clear sections and examples.

Deep technical documentation generation workflow using zen mcp's clink and docgen tools. First uses clink to launch gemini CLI in WSL for code analysis, then uses docgen for structured document generation with complexity analysis. Specializes in documents requiring deep understanding of code logic, model architecture, or performance bottleneck analysis. Use when user requests "use gemini for deep analysis", "generate architecture analysis document", "analyze performance bottlenecks", "deeply understand code logic", or similar deep analysis tasks. Default output is .md format.

Collaborative documentation and test code writing workflow using zen mcp's clink to launch gemini CLI session in WSL (via 'gemini' command) where all writing operations are executed. Use this skill when the user requests "use gemini to write test files", "use gemini to write documentation", "generate related test files", "generate an explanatory document", or similar document/test writing tasks. The gemini CLI session acts as the specialist writer, working with the main Claude model for context gathering, outline approval, and final review. For test code, codex CLI (also launched via clink) validates quality after gemini completes writing.

Intelligent skill router that analyzes user requests and automatically dispatches to the most appropriate skill(s) or zen-mcp tools. Routes to zen-chat for Q&A, zen-thinkdeep for deep problem investigation, codex-code-reviewer for code quality, simple-gemini for standard docs/tests, deep-gemini for deep analysis, or plan-down for planning. Use this skill proactively to interpret all user requests and determine the optimal execution path.

Analyzes code quality, complexity, and technical debt using PMAT(Pragmatic AI Labs MCP Agent Toolkit). Use this skill when:- User mentions "code quality", "complexity", "technical debt", or "maintainability"- Reviewing code or conducting code review- Modifying or refactoring existing code files- Creating pull requests or preparing commits- Investigating performance or quality issuesSupports 25+ languages including Rust, Python, TypeScript, JavaScript, Go, C++, Java, Ruby, PHP, Swift, and more.Provides cyclomatic complexity, cognitive complexity, maintainability index, dead code detection,and technical debt annotations (SATD: TODO, FIXME, HACK comments).

Tracks and manages technical debt using PMAT (Pragmatic AI Labs MCP Agent Toolkit).Use this skill when:- User asks about technical debt, TODO comments, or code quality issues- Planning sprint work and need to prioritize debt repayment- Conducting code audits or technical debt assessments- Tracking debt accumulation trends over time- Creating technical debt reports for stakeholdersDetects SATD (Self-Admitted Technical Debt) annotations: TODO, FIXME, HACK, XXX, NOTE comments.Provides debt quantification in hours, prioritization by severity, and repayment tracking.