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Found 12,031 Skills
Use this skill for reinforcement learning tasks including training RL agents (PPO, SAC, DQN, TD3, DDPG, A2C, etc.), creating custom Gym environments, implementing callbacks for monitoring and control, using vectorized environments for parallel training, and integrating with deep RL workflows. This skill should be used when users request RL algorithm implementation, agent training, environment design, or RL experimentation.
Manages context window optimization, session state persistence, and token budget allocation for multi-agent workflows. Use when dealing with token budget management, context window limits, session handoff, state persistence across agents, or /clear strategies. Do NOT use for agent orchestration patterns (use moai-foundation-core instead).
Orchestrates complete project initialization by coordinating agent-folder-init, linter-formatter-init, husky-test-coverage, and other setup skills. Use this skill when starting a new project that needs full AI-first development infrastructure with code quality enforcement.
Determine the best Anthropic architecture for your project by analyzing requirements and recommending the optimal combination of Skills, Agents, Prompts, and SDK primitives.
Validate skill directories against AgentSkills spec
Produce an LLM Build Pack (prompt+tool contract, data/eval plan, architecture+safety, launch checklist). Use for building with LLMs, GPT/Claude apps, prompt engineering, RAG, and tool-using agents.
Architecting real-time Voice AI agents.
Evaluates agent skills against Anthropic's best practices. Use when asked to review, evaluate, assess, or audit a skill for quality. Analyzes SKILL.md structure, naming conventions, description quality, content organization, and identifies anti-patterns. Produces actionable improvement recommendations.
Autonomous prior art search and analysis agent. Searches multiple databases, analyzes references, creates claim charts, and assesses patentability impact.
Autonomous Freedom to Operate analysis agent. Identifies blocking patents, assesses infringement risk, and recommends mitigation strategies for product commercialization.
Use this skill whenever the agent has access to Linkup web search or fetch tools. Teaches the agent how to reason about query construction, choose search depth, write effective queries, select the right output type, use the fetch endpoint, and apply advanced techniques like sequential search and multi-query coverage. Applicable to any task involving web search, content extraction, company research, news retrieval, data enrichment, or real-time information gathering via Linkup.
macOS system resource optimization with 40 specialized agents for memory, disk, CPU, and process management