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Found 11,814 Skills
Implements agents using Deep Agents. Use when building agents with create_deep_agent, configuring backends, defining subagents, adding middleware, or setting up human-in-the-loop workflows.
Plan-spec-implement workflow for structured development. Only use when explicitly directed by user or when mentioned in project AGENTS.md file. Generates ephemeral plans in ~/.dot-agent/, applies specs to project docs, then implements test-first.
Create agents for financial analysis, investment research, and portfolio management. Covers financial data processing, risk analysis, and recommendation generation. Use when building investment analysis tools, robo-advisors, portfolio trackers, or financial intelligence systems.
Working memory management, context prioritization, and knowledge retention patterns for AI agents. Use when you need to maintain relevant context and avoid information loss during long tasks.
Slack automation CLI for AI agents. Use when: - Reading a Slack message or thread (given a URL or channel+ts) - Downloading Slack attachments (snippets, images, files) to local paths - Searching Slack messages or files - Sending a reply or adding/removing a reaction - Fetching a Slack canvas as markdown - Looking up Slack users Triggers: "slack message", "slack thread", "slack URL", "slack link", "read slack", "reply on slack", "search slack"
Build LLM applications with LangChain and LangGraph. Use when creating RAG pipelines, agent workflows, chains, or complex LLM orchestration. Triggers on LangChain, LangGraph, LCEL, RAG, retrieval, agent chain.
Build LiveKit Agent backends in TypeScript or JavaScript. Use this skill when creating voice AI agents, voice assistants, or any realtime AI application using LiveKit's Node.js Agents SDK (@livekit/agents-js). Covers AgentSession, Agent class, function tools with zod, STT/LLM/TTS models, turn detection, and realtime models.
Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use only when explicitly invoked with "use browser agent" or "use agent browser".
Audits agent skill instructions and system prompts for vulnerabilities to prompt hijacking and indirect injection. Use when designing new agent skills or before deploying agents to public environments where users provide untrusted input.
The Meta-Skill. Use this to create NEW skills (tools) for the agent.
Expert blueprint for real-time strategy games including unit selection (drag box, shift-add), command systems (move, attack, gather), pathfinding (NavigationAgent2D with RVO avoidance), fog of war (SubViewport mask shader), resource economy (gather/build loop), and AI opponents (behavior trees, utility AI). Use for base-building RTS or tactical combat games. Trigger keywords: RTS, unit_selection, command_system, fog_of_war, pathfinding_RVO, resource_economy, command_queue.
Analyzes and improves LLM prompts and agent instructions for token efficiency, determinism, and clarity. Use when (1) writing a new system prompt, skill, or CLAUDE.md file, (2) reviewing or improving an existing prompt for clarity and efficiency, (3) diagnosing why a prompt produces inconsistent or unexpected results, (4) converting natural language instructions into imperative LLM directives, or (5) evaluating prompt anti-patterns and suggesting fixes. Applies to all LLM platforms (Claude, GPT, Gemini, Llama).