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Found 2,180 Skills
Letta framework for building stateful AI agents with long-term memory. Use for AI agent development, memory management, tool integration, and multi-agent systems.
Spawning Plan. Use when user wants to spawn agents, create a team, or coordinate multiple agents. Automatically gathers context, asks team topology questions, outputs clean TEAM PLAN markdown, and gets user approval. 3 steps: context gathering → questions → present plan. **CRITICAL**: MUST NOT SPAWN AGENTS SKIPPING THIS SKILL, USE ALWAYS.
Build multiple AI agents that work together. Use when you need a supervisor agent that delegates to specialists, agent handoff, parallel research agents, support escalation (L1 to L2), content pipeline (writer + editor + fact-checker), or any multi-agent system. Powered by DSPy for optimizable agents and LangGraph for orchestration.
Analyze other agents' sessions and construct targeted corrective prompts to fix mistakes, correct context drift, or drive home task requirements
Builds AI chat interfaces and conversational UI with streaming responses, context management, and multi-modal support. Use when creating ChatGPT-style interfaces, AI assistants, code copilots, or conversational agents. Handles streaming text, token limits, regeneration, feedback loops, tool usage visualization, and AI-specific error patterns. Provides battle-tested components from leading AI products with accessibility and performance built in.
Bidirectional agent team communication via the meet-ai chat server. Agents send and receive messages through the CLI, visible in the web UI.
Executes DAG waves with controlled parallelism using the Task tool. Manages concurrent agent spawning, resource limits, and execution coordination. Activate on 'execute dag', 'parallel execution', 'concurrent tasks', 'run workflow', 'spawn agents'. NOT for scheduling (use dag-task-scheduler) or building DAGs (use dag-graph-builder).
When the user wants to build GTM automation with code, design workflow architectures, use AI agents for GTM tasks, or implement the 'architecture over tools' principle. Also use when the user mentions 'GTM engineering,' 'GTM automation,' 'n8n,' 'Make,' 'Zapier,' 'workflow automation,' 'Clay API,' 'instruction stacks,' 'AI agents for GTM,' or 'revenue automation.' This skill covers technical GTM infrastructure from workflow design through agent orchestration.
Build container-based Foundry Agents using Azure AI Projects SDK with ImageBasedHostedAgentDefinition. Use when creating hosted agents that run custom code in Azure AI Foundry with your own container images. Triggers: "ImageBasedHostedAgentDefinition", "hosted agent", "container agent", "Foundry Agent", "create_version", "ProtocolVersionRecord", "AgentProtocol.RESPONSES", "custom agent image".
Proxmox Virtual Environment operational expertise for AI agents - VM lifecycle, LXC containers, storage management, backup strategies, HA configuration, and troubleshooting
Multi-Agent Architecture Design and Intelligent Spawn System. Use this skill when you need to design a multi-agent system, configure specialized agents, implement intelligent task distribution, or optimize concurrent processing capabilities.
Verification boundary CLI that delegates tasks to autonomous agents. Use when the user wants to run forge, execute specs, run specs in parallel, audit code against specs, review changes, watch live logs, check run status, resume a session, or delegate complex multi-step work to an autonomous agent. Triggers include "forge run", "run this spec", "run specs in parallel", "audit the codebase", "review changes", "forge watch", "forge status", "rerun failed", "delegate this to forge".