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Found 3,375 Skills
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".
Initialize projects with agentic coding structure. Use when setting up a new project, adding AI agent support to existing project, or when user says "init", "initialize", "setup project", or "scaffold". Creates AGENTS folder, documentation templates, and _NOTES scratch space.
Publish and query agent profiles on ATProto. Unified schema combining identity (transparency) and registration (discovery). Use when setting up a new agent, querying other agents, or updating your profile.
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.
Web UI testing and browser automation with Vercel agent-browser. Use when tasks require opening pages, interacting with forms, validating UI flows, taking screenshots, extracting page data, or running repeatable browser-based checks locally or in CI.
Use when implementing agent memory, persisting state across sessions, building knowledge graphs, tracking entities, or asking about "agent memory", "knowledge graph", "entity memory", "vector stores", "temporal knowledge", "cross-session persistence"
DigitalOcean Gradient AI agentic cloud and AI platform for building, training, and deploying AI agents on GPU infrastructure with foundation models, knowledge bases, and agent routes. Use when planning or operating AI agents on DigitalOcean.
Use this skill when you need to test or evaluate LangGraph/LangChain agents: writing unit or integration tests, generating test scaffolds, mocking LLM/tool behavior, running trajectory evaluation (match or LLM-as-judge), running LangSmith dataset evaluations, and comparing two agent versions with A/B-style offline analysis. Use it for Python and JavaScript/TypeScript workflows, evaluator design, experiment setup, regression gates, and debugging flaky/incorrect evaluation results.
Create slash commands for Claude Code with $ARGUMENTS handling, agent invocation patterns, and template best practices. Reference for building user-triggered workflow shortcuts.
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.
Configure which review agents run for your project. Auto-detects stack and writes compound-engineering.local.md.
Use when compressing agent context, implementing conversation summarization, reducing token usage in long sessions, or asking about "context compression", "conversation history", "token optimization", "context limits", "summarization strategies"