Claude Skills by majiayu000

Multi-agent workflow for editing Claude Code skills with quality gates

Create MicroPython applications for Universe 2025 (Tufty) Badge including display graphics, button handling, and MonaOS app structure. Use when building badge apps, creating interactive displays, or developing MicroPython programs.

Deployment workflows, file management, and project organization for Universe 2025 (Tufty) Badge. Use when deploying apps to MonaOS, managing files on device, syncing projects, organizing code, or setting up deployment pipelines.

System diagnostics, verification, and troubleshooting for Badger 2350. Use when checking firmware version, verifying installations, diagnosing hardware issues, troubleshooting errors, or performing system health checks on Badger 2350.

Hardware integration for Badger 2350 including GPIO, I2C sensors, SPI devices, and electronic components. Use when connecting external hardware, working with sensors, controlling LEDs, reading buttons, or interfacing with I2C/SPI devices on Badger 2350.

Complete getting started guide for Universe 2025 (Tufty) Badge from zero to first app. Use when helping absolute beginners, providing step-by-step first-time setup, or when users ask "how do I get started", "where do I begin", or "first steps with the badge".

Organize the hive that Bee collected. The badger methodically sorts issues into project columns, assigns sizes and priorities, moves work from backlog to ready, and plans milestones. Use when you need to triage your GitHub project board, size issues, set priorities, or plan timelines.

🐟 Rust-native Fish shell-friendly file operations with Steel-backed SCI

Guide for balancing new Heart Rush content including talents, races, bloodmarks, and progression. Use when creating or modifying game mechanics to ensure they fit the existing power curve.

Generate alignment statistics using samtools flagstat, stats, depth, and coverage. Use when assessing alignment quality, calculating coverage, or generating QC reports.

Manage small business HR with BambooHR's people management platform.

Generates production-ready BAML applications from natural language requirements. Creates complete type definitions, functions, clients, tests, and framework integrations for data extraction, classification, RAG, and agent workflows. Queries official BoundaryML repositories via MCP for real-time patterns. Supports multimodal inputs (images, audio), 6 programming languages (Python, TypeScript, Ruby, Java, Go, C#), 10+ frameworks, 50-70% token optimization, and 95%+ compilation success.

Generic BAML patterns for type-safe LLM prompting. Covers schema design, DTO generation, client wrappers, and cross-language codegen. Framework-agnostic.

Generate images using Google's Gemini image generation model with Deno. Use this skill when the user wants to create AI-generated images, perform image-to-image transformations, or generate visual content from text prompts. Triggers include requests like "generate an image of...", "create a picture of...", "make an image with...", or "transform this image to...".

This skill should be used when building automated trading systems, implementing limit orders, or adding DCA/TWAP functionality. Covers limit orders, stop losses, DCA schedules, and TWAP execution.

This skill should be used when the user asks to "implement Bankr client", "write bankr-client.ts", "create API client for Bankr", "common files for Bankr project", "package.json for Bankr", "tsconfig for Bankr", "Bankr TypeScript patterns", "Bankr response types", or needs the reusable client code and common project files for Bankr API integrations.

This skill should be used when encountering authentication errors, API key errors, 401 errors, "invalid API key", "BANKR_API_KEY not set", job failures, or any Bankr API errors. Provides setup instructions and troubleshooting guidance for resolving Bankr configuration issues.

This skill should be used when executing Bankr requests, submitting prompts to Bankr API, polling for job status, checking job progress, using Bankr MCP tools, or understanding the submit-poll-complete workflow pattern. Provides the core asynchronous job pattern for all Bankr API operations.

This skill should be used when building perpetual trading bots, implementing leverage functionality, or adding position management. Covers Avantis integration, long/short positions, and risk controls.

This skill should be used when building market data displays, implementing price feeds, or adding technical analysis. Covers prices, market caps, technical analysis, sentiment, and trending tokens.

This skill should be used when building NFT marketplace integrations, implementing collection browsing, or adding floor price tracking. Covers OpenSea integration, floor prices, and NFT purchases.

This skill should be used when the user asks about "Polymarket", "prediction markets", "betting odds", "place a bet", "check odds", "market predictions", "what are the odds", "bet on election", "sports betting", or any prediction market operation. Provides guidance on searching markets, placing bets, and managing positions.

This skill should be used when building portfolio dashboards, implementing balance checking, or adding multi-chain holdings views. Covers balances, holdings, and valuations across chains.

This skill should be used when the user asks to "scaffold a Bankr project", "create new Bankr bot", "build a Bankr web service", "create Bankr dashboard", "build Bankr CLI tool", "project structure for Bankr", "Bankr project types", or needs guidance on directory structures and templates for different types of Bankr API integrations.

This skill should be used when building trading bots, implementing swap functionality, or adding cross-chain bridge support. Covers same-chain swaps, cross-chain bridges, ETH/WETH conversions, and amount formats.

This skill should be used when building payment systems, implementing token transfers, or adding ENS/social handle resolution. Supports wallet addresses, ENS names, and social handles.

Los usuarios han aprendido a ignorar todo lo que parece un anuncio, incluso cuando contiene información relevante. Esto incluye elementos con colores brillantes, posicionados en zonas típicas de ads, o con formato de banner.

Knowledge comic creator supporting multiple art styles and tones. Creates original educational comics with detailed panel layouts and sequential image generation. Use when user asks to create "知识漫画", "教育漫画", "biography comic", "tutorial comic", or "Logicomix-style comic".

Cross-platform image compression skill. Converts images to WebP by default with PNG-to-PNG support. Uses system tools (sips, cwebp, ImageMagick) with Sharp fallback.

Generates article cover images with 20 hand-drawn styles and auto-style selection. Supports cinematic (2.35:1), widescreen (16:9), and square (1:1) aspects. Use when user asks to "generate cover image", "create article cover", "make cover", or mentions "封面图".

Convert X (Twitter) tweet or article URL to markdown. Uses reverse-engineered X API (private). Requires user consent before use.

Post content to WeChat Official Account (微信公众号). Supports both article posting (文章) and image-text posting (图文).

Posts content and articles to X (Twitter). Supports regular posts with images/videos and X Articles (long-form Markdown). Uses real Chrome with CDP to bypass anti-automation. Use when user asks to "post to X", "tweet", "publish to Twitter", or "share on X".

Generate professional slide deck images from content. Creates comprehensive outlines with style instructions, then generates individual slide images. Use when user asks to "create slides", "make a presentation", "generate deck", or "slide deck".

Generates Xiaohongshu (Little Red Book) infographic series with 9 visual styles and 6 layouts. Breaks content into 1-10 cartoon-style images optimized for XHS engagement. Use when user mentions "小红书图片", "XHS images", "RedNote infographics", "小红书种草", or wants social media infographics for Chinese platforms.

Create LangChain agents with create_agent, define tools, and use middleware for human-in-the-loop and error handling.

Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern. Used in production at LinkedIn, Uber, and 400+ companies. This is LangChain's recommended approach for building agents. Use when: langgraph, langchain agent, stateful agent, agent graph, react agent.

Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern. Used in production at LinkedIn, Uber, and 400+ companies. This is LangChain's recommended approach for building agents. Use when: langgraph, langchain agent, stateful agent, agent graph, react agent.

Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern. Used in production at LinkedIn, Uber, and 400+ companies. This is LangChain's recommended approach for building agents. Use when: langgraph, langchain agent, stateful agent, agent graph, react agent.

Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern. Used in production at LinkedIn, Uber, and 400+ companies. This is LangChain's recommended approach for building agents. Use when: langgraph, langchain agent, stateful agent, agent graph, react agent.

Convert legacy subagents, slash commands, and rules to the unified Agent Skills format. Use when migrating agent resources, consolidating legacy directories, or standardizing across Claude Code, Cursor, Copilot, Codex, and Open Code.

Convert legacy subagents, slash commands, and rules to the unified Agent Skills format. Use when migrating agent resources, consolidating legacy directories, or standardizing across Claude Code, Cursor, Copilot, Codex, and Open Code.

Canonical Claude Code authoring kit covering Skills, sub-agents, plugins, slash commands, hooks, memory, settings, sandboxing, headless mode, and advanced agent patterns. Use when creating Claude Code extensions or configuring Claude Code features.

MoAI super agent - unified orchestrator for autonomous development. Routes natural language or explicit subcommands (plan, run, sync, fix, loop, project, feedback) to specialized agents. Use for any development task from planning to deployment.

This skill should be used when guiding the OpenAI agent to map natural language user input to appropriate MCP tools, handling phrases like "Add task" → add_task, "List pending" → list_tasks(status="pending"), tool chains, and extracting user email from JWT.

This skill should be used when guiding the OpenAI agent to map natural language user input to appropriate MCP tools, handling phrases like "Add task" → add_task, "List pending" → list_tasks(status="pending"), tool chains, and extracting user email from JWT.

This skill should be used when guiding the OpenAI agent to map natural language user input to appropriate MCP tools, handling phrases like "Add task" → add_task, "List pending" → list_tasks(status="pending"), tool chains, and extracting user email from JWT.

This skill should be used when guiding the OpenAI agent to map natural language user input to appropriate MCP tools, handling phrases like "Add task" → add_task, "List pending" → list_tasks(status="pending"), tool chains, and extracting user email from JWT.

Build AI agents with OpenAI Agents SDK + Model Context Protocol (MCP) for tool orchestration. Supports multi-provider backends (OpenAI, Gemini, Groq, OpenRouter) with MCPServerStdio. Use this skill for conversational AI features with external tool access via MCP protocol.

Expert guidance for building multi-agent AI applications using the OpenAI Agents SDK for Python. Use when (1) creating agents with handoffs, tools, guardrails, or sessions, (2) implementing structured outputs with Pydantic models, (3) building agentic workflows, (4) debugging and tracing agent execution, (5) working with provider-agnostic LLM applications (OpenAI, Anthropic, LiteLLM), or (6) implementing customer support, legal research, financial analysis, or autonomous task completion systems.