Claude Skills by majiayu000

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.

Generate a complete OAF-compliant agent package from an Agent Case (requirements) and Agent Design (architecture). Use when asked to "package an agent", "generate an agent package", "create an agent from a design", or when you have both case/ and design/ folders and need to create the package/ folder with AGENTS.md, skills, and scripts.

Guide for using pagent - a PRD-to-code orchestration tool. Use when users ask how to use pagent, run agents, create PRDs, or transform requirements into code.

Guide for using pagent - a PRD-to-code orchestration tool. Use when users ask how to use pagent, run agents, create PRDs, or transform requirements into code.

Guidance for working with the PolicyEngine GitHub agent bot

Become an autonomous prediction market trader on Polymarket with AI-powered analysis and a performance-backed token on Base. Trade real markets, build a track record, and let the buyback flywheel run.

This skill should be used when users want to create powerful AI agents comparable to Claude Code or sonph-code. It provides battle-tested system prompts, masterfully-crafted tool implementations, and the simple but powerful agent loop pattern. Use this skill when users ask to build coding agents, AI assistants with tools, or any autonomous agent that needs file operations, code execution, search, and task management capabilities. The key insight is that customization requires only ONE HumanMe...

Anticipates and pre-loads optimal skills before task execution based on pattern matching and historical success rates

Create and manage agentic wallets with Privy. Use for autonomous onchain transactions, wallet creation, policy management, and transaction execution on Ethereum, Solana, and other chains. Triggers on requests involving crypto wallets for AI agents, server-side wallet operations, or autonomous transaction execution.

Transform AI agents from task-followers into proactive partners that anticipate needs and continuously improve. Includes memory architecture with pre-compaction flush (so context survives when the window fills), reverse prompting (surfaces ideas you didn't know to ask for), security hardening, self-healing patterns (diagnoses and fixes its own issues), and alignment systems (stays on mission, remembers who it serves). Battle-tested patterns for agents that learn from every interaction and cre...

Patterns and workflows for proactive agent behavior.

Operate an AI agent inside OpenClaw World over HTTP IPC. Use when tasks involve registering or reconnecting an agent, moving, chatting, forming alliances, running turn-based combat, checking world phase/state, or handling survival and betting commands.

Python Agent 开发规范（Windows wxauto v4），包括项目结构、模块化、wxauto 使用、IPC 集成、错误处理、测试和部署。

Show AgentOps next action.

持久化执行-验证-修复循环，直到任务完成

Specification-first AI development powered by Ouroboros. Socratic questioning exposes hidden assumptions before writing code. Evolutionary loop (Interview → Seed → Execute → Evaluate → Evolve) runs until ontology converges. Ralph mode persists until verification passes — the boulder never stops. Use when user says \"ralph\", \"ooo\", \"don't stop\", \"must complete\", \"until it works\", \"keep going\", \"interview me\", or \"stop prompting\".

Enables autonomous development loops that run until all tasks pass. Use when the user says "until done", "keep going", "finish this", "終わるまでやれ", or requests long-running autonomous iteration with fix_plan.md tracking.

Use this skill when Ralph is working autonomously through Brain Dump backlogs. Covers ticket selection, implementation patterns, and autonomous workflow management.

Run Ralph autonomous build loop. Use when user asks to "ralph build", "run build loop", or needs to process subtasks autonomously. Executes iterations against a subtasks.json queue.

Create and run Ralph loops for structured AI-driven development. Triggered by "create a ralph loop for X" or "ralph plan for X". Uses interview to clarify requirements, expert review via Ralph wrappers, creates phased task plans, and executes in YOLO mode.

Self-referential loop until task completion with architect verification

Persistent completion mode. Use when the user explicitly says `/ralph` or clearly wants you to keep iterating until the task is actually finished, repeating implement-verify-fix loops instead of stopping at partial progress.

Run RALPH autonomous development loop. Converts PRD markdown to prd.json and runs autonomous implementation.

Run RALPH autonomous development loop. Converts PRD markdown to prd.json and runs autonomous implementation.

Autonomous execution loop that processes a Beads epic task-by-task with fresh subagents, two-stage review, and circuit breaker safety. Use after plan-to-epic creates the epic.

Execute iterative development loop through user stories. Implements one story at a time with quality gates, commits, and learning persistence. Ships features autonomously.

Execute Ralph loops. Use when: Running the autonomous loop, managing tasks, or handling backpressure. Not for: Designing new loops or defining high-level strategy.

Convert PRDs to prd.json format and run the Ralph autonomous agent system. Use when converting PRDs to Ralph format OR running Ralph to execute user stories. Triggers on: convert this prd, turn this into ralph format, create prd.json, ralph json, run ralph, start ralph, execute ralph.

Runs autonomous loop fetching stories from GitHub Issues. Implements and closes issues as done. Triggers on "loop through my PRDs", "work on my issues", "start the autonomous loop", "implement my PRDs", or requests to work through GitHub issues autonomously.

Convert PRDs to prd.json format for the Ralph autonomous agent system. Use when you have an existing PRD and need to convert it to Ralph's JSON format. Triggers on: convert this prd, turn this into ralph format, create prd.json from this, ralph json.

Convert PRDs to prd.json format for the Ralph autonomous agent system. Use when you have an existing PRD and need to convert it to Ralph's JSON format. Triggers on: convert to ralph, convert this prd, turn this into ralph format, create prd.json, ralph json, run ralph on this.

Converts a PRD or plan markdown file into prd.json format for ralph-json-start-loop to execute autonomously. Use when user wants to convert a PRD or plan to JSON stories.

Runs the Ralph autonomous loop. Executes stories from prds/*.json using git worktrees.