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Found 892 Skills
OpenAI Codex Rust coding patterns distilled from the codex-rs workspace. Use this skill whenever writing, reviewing, or refactoring Rust code — especially for async agents, CLI tools, sandboxing, Ratatui TUIs, JSON-RPC protocols, tokio-based services, or any codebase that needs defensive panic discipline. Trigger even when the user does not explicitly mention Codex, because the patterns generalize to any production Rust workspace. Covers async cancellation, error enum design, process sandboxing, Cargo workspace architecture, wiremock-based fakes, insta snapshot testing, OpenTelemetry tracing, and Ratatui rendering.
Use when learning Rust concepts. Keywords: mental model, how to think about ownership, understanding borrow checker, visualizing memory layout, analogy, misconception, explaining ownership, why does Rust, help me understand, confused about, learning Rust, explain like I'm, ELI5, intuition for, coming from Java, coming from Python, 心智模型, 如何理解所有权, 学习 Rust, Rust 入门, 为什么 Rust
Use when structuring app entry points, managing authentication flows, switching root views, handling scene lifecycle, or asking 'how do I structure my @main', 'where does auth state live', 'how do I prevent screen flicker on launch', 'when should I modularize' - app-level composition patterns for iOS 26+
Python backend implementation patterns for FastAPI applications with SQLAlchemy 2.0, Pydantic v2, and async patterns. Use during the implementation phase when creating or modifying FastAPI endpoints, Pydantic models, SQLAlchemy models, service layers, or repository classes. Covers async session management, dependency injection via Depends(), layered error handling, and Alembic migrations. Does NOT cover testing (use pytest-patterns), deployment (use deployment-pipeline), or FastAPI framework mechanics like middleware and WebSockets (use fastapi-patterns).
Explains code with visual diagrams and analogies. Use when explaining how code works, teaching about a codebase, or when the user asks "how does this work?"
Guide for building UI with Base UI React (@base-ui/react), a headless, accessible component library using compound component patterns. Use this skill whenever the user is building or modifying any user interface in React, including forms and validation, navigation and menus, modals and overlays, selection controls, toast notifications, accordions, tabs, or any interactive UI component. Also trigger when the user mentions @base-ui/react, Base UI, headless components, migrating from Radix UI, or asks about accessible component patterns. Even if the user does not explicitly mention Base UI, use this skill whenever they are creating React UI components, building a design system, or working on frontend user experience.
Deep test, analyze, and audit Claude skills. Use this skill whenever the user wants to test a skill's behavior, analyze how it uses the Claude API, inspect inputs/outputs from scripts, or run security and code review audits against skill scripts. Trigger on: "test my skill", "analyze this skill", "audit skill scripts", "review skill for security issues", "what does this skill actually do when it runs", "inspect API calls from skill", "run a skill through its paces", "check my skill for bugs or vulnerabilities". Also trigger when the user shows you a SKILL.md and asks you to evaluate, critique, or stress-test it.
Vitest testing framework patterns for test setup, async testing, mocking with vi.*, snapshots, and test performance (formerly test-vitest). This skill should be used when writing or debugging Vitest tests. This skill does NOT cover TDD methodology (use test-tdd skill), API mocking with MSW (use test-msw skill), or Jest-specific APIs.
Use when the user wants to review a pull request, understand what a PR changes, assess risk of merging, or check for missing test coverage. Examples: "Review this PR", "What does PR #42 change?", "Is this PR safe to merge?"
Integrate Mem0 Platform into AI applications for persistent memory, personalization, and semantic search. Use this skill when the user mentions "mem0", "memory layer", "remember user preferences", "persistent context", "personalization", or needs to add long-term memory to chatbots, agents, or AI apps. Covers Python and TypeScript SDKs, framework integrations (LangChain, CrewAI, Vercel AI SDK, OpenAI Agents SDK, Pipecat), and the full Platform API. Use even when the user doesn't explicitly say "mem0" but describes needing conversation memory, user context retention, or knowledge retrieval across sessions.
Team-wide memory routing skill — routes agent queries to the optimal knowledge source (QMD hybrid search, daily memory, MEMORY.md) and enforces citation. Use when any agent needs to retrieve prior work, system config, skill docs, project status, or decisions. Triggers on "查知识库", "memory router", "qmd query", "find in docs", "what was decided", "how does X work", "项目状态", "之前的决策".
Interactive onboarding tour for the context-matic MCP server. Walks the user through what the server does, shows all available APIs, lets them pick one to explore, explains it in their project language, demonstrates model_search and endpoint_search live, and ends with a menu of things the user can ask the agent to do. USE FOR: first-time setup; "what can this MCP do?"; "show me the available APIs"; "onboard me"; "how do I use the context-matic server"; "give me a tour". DO NOT USE FOR: actually integrating an API end-to-end (use integrate-context-matic instead).