Claude Code Skills · page 137

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Academic English consistency linting and non-native (ESL) language polish for medical manuscripts. Deterministically flags abbreviation define-once violations, US/UK spelling drift, hyphen-vs-en-dash numeric ranges, P/p case, hyphenation variants, small-number style, and value/unit spacing, then guides a style-only clarity pass that never alters numbers, citations, or scientific meaning. Distinct from humanize (AI-tell removal) and check-reporting (guideline items).

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Turn a folder of research PDFs into an Obsidian knowledge vault — consistently formatted literature notes with frontmatter, PDF embed links, and cross-referenced atomic concept notes. Use whenever the user wants PDFs converted to Obsidian notes, a batch of papers summarized into a common template, a research "second brain" built or extended, or concepts extracted across accumulated notes — even if they never say "Obsidian". Pairs with /lit-sync, which owns the same vault folders from the Zotero/BibTeX side.

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Comprehensive kanban board and task management via ktui CLI. Use for project tracking, todo lists, task dependencies, workflow automation, and board management. Activates when user mentions boards, tasks, kanban, or project management. If the `ktui` command is not available, but `uv` is available utilize `uvx kanban-tui` instead.

帮助学生在临考前进行结构化极速复习：解析课程资料/大纲/重点，按章节生成 wiki 知识库与标准题库，组织针对性刷题与判分，并记录复习进度和错题。当用户即将考试、需要快速复习计划、练习题、错题复盘或考前小抄时使用（关键词：期末/备考/复习/刷题/划重点/错题；exam, cram, study plan, quiz, review）。不适用于长期学习规划、与考试无关的写作或编程任务。

教学过程中自动捕获和记录学习者的概念疑难点（"为什么/是什么/怎么推/什么意思"类型的问题），保存到进度文件的"概念疑难点记录"区，形成考前回顾清单。

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将已经讲完但尚未完成阶段门禁的一个章节整理成强类型教材清单，并在视觉模式下编译为公式可读、图片可见、知识点与全部对应例题逐项精讲的自包含 HTML/PDF。结构化工作区准备阶段完成证据、用户说 Markdown 公式仍是 raw LaTeX、图片缺失、要含课件/作业/Quiz/模拟考试题及答案的零基础讲义，或要求打印版时使用。

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Common agent patterns and templates for Claude Code. Use when implementing agents to follow proven patterns for Tasks integration, quality checks, and external model invocation via claudish CLI.

YAML frontmatter schemas for Claude Code agents and commands. Use when creating or validating agent/command files.

XML tag structure patterns for Claude Code agents and commands. Use when designing or implementing agents to ensure proper XML structure following Anthropic best practices.

YAML format for Claude Code agent definitions as alternative to markdown. Use when creating agents with YAML, converting markdown agents to YAML, or validating YAML agent schemas. Trigger keywords - "YAML agent", "agent YAML", "YAML format", "agent schema", "YAML definition", "convert to YAML".

Linear API patterns and examples for autopilot. Includes authentication, webhooks, issue CRUD, state transitions, file attachments, and comment handling.

Proof artifact generation patterns for task validation. Covers screenshots, test results, deployments, and confidence scoring.

Task lifecycle state transitions with validation gates. Defines states, triggers, and required proofs.

How tag-to-command routing works in autopilot. Defines default mappings, precedence rules, and customization patterns.

CRITICAL - Guide for using Claudish CLI ONLY through sub-agents to run Claude Code with OpenRouter models (Grok, GPT-5, Gemini, MiniMax). NEVER run Claudish directly in main context unless user explicitly requests it. Use when user mentions external AI models, Claudish, OpenRouter, or alternative models. Includes mandatory sub-agent delegation patterns, agent selection guide, file-based instructions, and strict rules to prevent context window pollution.

Use when analyzing architecture and system design. Find design patterns, map layers, identify core abstractions via PageRank. Uses claudemem AST structural analysis for efficient architecture investigation.

Use when orchestrating multi-agent code analysis with claudemem. Run claudemem once, share output across parallel agents. Enables parallel investigation, consensus analysis, and role-based command mapping.

⚡ PRIMARY TOOL for semantic code search AND structural analysis. NEW: AST tree navigation with map, symbol, callers, callees, context commands. PageRank ranking. Recommended workflow: Map structure first, then search semantically, analyze callers before modifying.

💡 Tool selector for code search tasks. Helps choose between semantic search (claudemem) and native tools (Grep/Glob) based on query type. Semantic search recommended for: 'how does X work', 'find all', 'audit', 'investigate', 'architecture'.

Use when integrating detective skills across plugins. Maps agent roles to appropriate detective skills (developer → developer-detective, architect → architect-detective). Reference this to connect agents with claudemem investigation capabilities.

⚡ Debugging skill. Best for: 'why is X broken', 'find bug source', 'root cause analysis', 'trace error', 'debug issue'. Uses claudemem AST with context command for efficient call chain analysis.

⚡ PRIMARY SKILL for: 'how does X work', 'investigate', 'analyze architecture', 'trace flow', 'find implementations'. PREREQUISITE: code-search-selector must validate tool choice. Launches codebase-detective with claudemem INDEXED MEMORY.

⚡ Implementation analysis skill. Best for: 'how does X work', 'find implementation of', 'trace data flow', 'where is X defined', 'find all usages'. Uses claudemem AST with callers/callees for efficient code tracing.

Unified entry point for code investigation. Auto-routes to specialized detective based on query keywords. Use when investigation type is unclear or for general exploration.

💡 Bulk file read optimizer. Suggests semantic search alternatives when reading multiple files. Helps reduce token usage by using claudemem's ranked results instead of sequential file reads.

⚡ Test analysis skill. Best for: 'what's tested', 'find test coverage', 'audit test quality', 'missing tests', 'edge cases'. Uses claudemem AST with callers analysis for efficient test discovery.

⚡ Comprehensive analysis skill. Best for: 'comprehensive audit', 'deep analysis', 'full codebase review', 'multi-perspective investigation', 'complex questions'. Combines all perspectives (architect+developer+tester+debugger). Uses Opus model with full claudemem AST analysis.

Get help with Conductor - commands, usage examples, and best practices

Execute tasks from track plan with TDD workflow and git commit integration

Create development track with spec and hierarchical plan through interactive Q&A

Git-aware logical undo at track, phase, or task level with confirmation gates

Initialize Conductor with product.md, tech-stack.md, and workflow.md

Show active tracks, progress, current tasks, and blockers

Architecture Decision Records (ADR) documentation practice. Use when documenting architectural decisions, recording technical trade-offs, creating decision logs, or establishing architectural patterns. Trigger keywords - "ADR", "architecture decision", "decision record", "trade-offs", "architectural decision", "decision log".

On-demand security and code quality audit. Use when checking for vulnerabilities, security issues, code smells, or compliance problems. Trigger keywords - "audit", "security check", "vulnerability scan", "code quality", "compliance", "security audit".

Use when designing REST or GraphQL APIs, defining endpoints, implementing pagination/filtering, handling API versioning, or establishing API documentation with OpenAPI/Swagger.

Use when implementing authentication (JWT, sessions, OAuth), authorization (RBAC, ABAC), password hashing, MFA, or security best practices for backend services.

Use when creating OpenAPI specs for Bun.js APIs, integrating with Apidog, documenting endpoints with schemas, or automating API specification imports via Apidog REST API. See bunjs for basics.

Use when implementing clean architecture (routes/controllers/services/repositories), establishing camelCase conventions, designing Prisma schemas, or planning structured workflows for Bun.js applications. See bunjs for basics, bunjs-production for deployment.

Use when deploying Bun.js to production, containerizing with Docker, setting up AWS ECS/Fargate, implementing Redis caching, hardening security, or configuring CI/CD pipelines. See bunjs for basics, bunjs-architecture for patterns.

Use when building Bun.js/Hono applications, implementing HTTP endpoints, setting up Prisma/SQLite, writing Zod validation, or using Bun's test runner. See bunjs-architecture for layered patterns, bunjs-production for deployment.

Use when designing database schemas, implementing repository patterns, writing optimized queries, managing migrations, or working with indexes and transactions for SQL/NoSQL databases.

Use when working with Dingo meta-language for Go, implementing optionals/results, using generics shortcuts, or transpiling .dingo files to .go while maintaining Go compatibility.

Use when implementing custom error classes, error middleware, structured logging, retry logic, or graceful shutdown patterns in backend applications.

Use when profiling Go applications (pprof), running benchmarks, optimizing memory/CPU usage, or debugging performance bottlenecks in production Go code.

Use when building Go backend services, implementing goroutines/channels, handling errors idiomatically, writing tests with testify, or following Go best practices for APIs/CLI tools.

Use when building FastAPI applications, implementing async endpoints, setting up Pydantic schemas, working with SQLAlchemy, or writing pytest tests for Python backend services.

Use when building Axum applications, implementing type-safe handlers, working with SQLx, setting up error handling with thiserror, or writing Rust backend services.

Use when detecting project technology stack from files/configs/directory structure, auto-loading framework-specific skills, or analyzing multi-stack fullstack projects (e.g., React + Go).

Use when troubleshooting bugs, analyzing stack traces, using debugging tools (breakpoints, loggers), or applying systematic debugging methodology across any technology stack.

Use when writing tests, setting up test frameworks, implementing mocking strategies, or establishing testing best practices (unit, integration, E2E) across any technology stack.

Use when implementing language-agnostic patterns like layered architecture, dependency injection, error handling, or code organization principles across any technology stack.

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Use when deciding whether to launch an agent, selecting which agent to use, or coordinating multiple agents. Covers delegation criteria, external-model patterns, task isolation, and agent selection strategies.

Use when debugging failures, errors, or unexpected behavior. Covers root cause investigation, data flow tracing, hypothesis-driven debugging, and fix verification to prevent trial-and-error approaches.

Use when writing production code. Enforces RED-GREEN-REFACTOR cycle: write failing test, make it pass, improve design. Prevents test-after development and ensures verified behavior.

Use when claiming task completion or marking items as done. Covers completion evidence requirements, verification methods, and anti-rationalization patterns.

Use when starting isolated feature work or before executing implementation plans. Manages full worktree lifecycle from creation through cleanup with safety checks and error recovery.

Use when writing README files, API documentation, user guides, or technical documentation following industry standards from Google, Microsoft, and GitLab style guides.

Evidence-based phase completion enforcement for /dev:feature. Use when orchestrating 8-phase feature development to ensure artifacts exist before phase completion, validation criteria are addressed, outer loops are enforced, and show-your-work requirements are met.

Systematically tests UI functionality, validates design fidelity with AI visual analysis, monitors console output, tracks network requests, and provides debugging reports using Chrome Extension MCP tools. Use after implementing UI features, for design validation, when investigating console errors, for regression testing, or when user mentions testing, browser bugs, console errors, or UI verification.

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Modern React 19+ patterns with TypeScript including function components, hooks, state management, TanStack Query integration, form handling with Zod, error boundaries, and performance optimization. Use when building React applications, implementing components, or setting up state management.

shadcn/ui component library patterns. Covers CLI usage, installation, component categories, theming with CSS variables, dark mode setup, and integration with React Hook Form + Zod. Use when adding UI components, setting up design systems, or implementing forms with shadcn/ui.

Use when choosing state management solutions, implementing global stores (Zustand, Pinia), managing server state (TanStack Query), or handling URL state in frontend applications across React and Vue.

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Comprehensive TanStack Query v5 patterns for async state management. Covers breaking changes, query key factories, data transformation, mutations, optimistic updates, authentication, testing with MSW, and anti-patterns. Use for all server state management, data fetching, and cache invalidation tasks.

TanStack Router patterns for type-safe, file-based routing. Covers installation, route configuration, typed params/search, layouts, and navigation. Use when setting up routes, implementing navigation, or configuring route loaders.

Use when writing component tests, testing user interactions, mocking APIs, or setting up Vitest/React Testing Library/Vue Test Utils for frontend applications.

Use when building Vue 3 applications with TypeScript, implementing Composition API components, setting up Pinia stores, or working with Vue Router. Covers script setup, composables, and reactive state.