Total 56,899 skills, AI & Machine Learning has 9462 skills
Showing 12 of 9462 skills
Design and build AI agents for any domain. Use when users: (1) ask to "create an agent", "build an assistant", or "design an AI system" (2) want to understand agent architecture, agentic patterns, or autonomous AI (3) need help with capabilities, subagents, planning, or skill mechanisms (4) ask about Claude Code, Cursor, or similar agent internals (5) want to build agents for business, research, creative, or operational tasks Keywords: agent, assistant, autonomous, workflow, tool use, multi-step, orchestration
AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.
Converting markdown plans into beads (tasks with dependencies) and polishing them until they're implementation-ready. The bridge between planning and agent swarm execution. Includes exact prompts used.
Generate images using Google Gemini's image generation capabilities. Use this skill when the user needs to create, generate, or produce images for any purpose including UI mockups, icons, illustrations, diagrams, concept art, placeholder images, or visual representations.
Enables Claude to manage LinkedIn posts, profile, and professional networking through browser automation
Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability.
Enables Claude to conduct comprehensive research using Gemini Deep Research for in-depth analysis and reports
Build interactive chat agents for exploring and discussing academic research papers from ArXiv. Covers paper retrieval, content processing, question-answering, and research synthesis. Use when building research assistants, paper summarization tools, academic knowledge bases, or scientific literature chatbots.
This guide applies when designing, writing, or structuring AI courses, tutorials, lectures, and hands-on projects. It is also to be used when users request to create syllabi, write lecture notes, or design coding exercises related to AI/ML/LLM topics.
Agent Teams Orchestration Playbook for Claude Code. This skill should be used when the user requests to "create agent teams", "use agent swarm", "set up multi-agent collaboration", "orchestrate agents", "coordinate parallel agents", "organize team collaboration", "build agent teams", "implement swarm orchestration", "set up multi-agent system", "coordinate agent collaboration", or needs guidance on adaptive team formation, quality gates, skill discovery, task distribution, team coordination strategies, or Agent Teams best practices. It should also be used when the user mentions terms like "multi-agent", "agent collaboration", "agent orchestration", "parallel agents", "divisional collaboration", "assemble a team", "put together a team", "multi-agent collaboration", "swarm orchestration", "agent team". Note: "swarm" is a generic industry term; Claude Code's official concept is "Agent Teams".
Builds sustained high agency through internalized standards, identity anchoring, cross-session learning, and self-recovery — all delivered in corporate PUA rhetoric. This is the evolution of PUA: same pressure culture, but with an internal engine that never burns out. Apply it to all tasks to maintain constant high agency. It is especially valuable for complex multi-step tasks, long debugging sessions, quality-sensitive deliverables, tasks requiring initiative and ownership, or whenever sustained motivation is critical. It can operate standalone or be stacked with PUA — when stacked, this skill's Recovery Protocol activates before PUA's L1 pressure takes effect. Trigger scenarios: start of any task, sustained work sessions, multi-turn problem-solving, or when you need the agent to think as an owner rather than a tool.
MindOS Knowledge Base Operation Guide (Chinese) for Agent tasks on local markdown/csv knowledge bases. It should be automatically triggered whenever tasks involve note files, SOP/workflow documents, profile/context documents, CSV tables, knowledge base organization, cross-Agent handover or decision synchronization, and are executed via the MindOS MCP tool. Typical requests include "update notes", "search knowledge base", "organize files", "execute SOP", "review according to team standards", "hand over tasks to another Agent", "synchronize decisions", "append to CSV", "retrospect this conversation", "extract key experiences", "adaptively update retrospective results to corresponding documents", "route this information to corresponding files", "synchronously update all related documents", etc.; it should be triggered even if the user does not explicitly mention MindOS.