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Found 268 Skills
Integrate PICA into an application using the OpenAI Agents SDK. Use when adding PICA tools to an OpenAI agent via @openai/agents, setting up PICA MCP with the OpenAI Agents SDK, or when the user mentions PICA with OpenAI Agents.
Create and maintain AI coding agent subagents (.claude/agents/*.md, .codex/agents/*.md) with YAML frontmatter (name/description/tools/model/permissionMode/skills/hooks), least-privilege tool selection, delegation patterns (Task), context budgeting, and safety best practices.
Create and improve OpenAkita skills. It is used when you need to: (1) create new skills for repetitive tasks, (2) improve existing skills, (3) encapsulate temporary scripts into reusable skills. Skills are the core mechanism of OpenAkita's self-evolution.
Build AI agents and automate Claude Code programmatically using the Claude Agent SDK and headless CLI mode. Use this skill when you need to build an agent, create a Claude agent, make a bot, work with the agent SDK, run Claude in headless mode, write programmatic agent code, automate with Claude, create an MCP server builder, or query Claude programmatically. Covers the Python SDK, the claude -p headless interface, custom tool creation with SDK MCP servers, hooks for deterministic control, session management, and CLI flag reference. Authentication uses existing ~/.claude/ config — no API keys required.
Design, create, and configure orq.ai Agents with tools, instructions, knowledge bases, and memory stores. Use when building new agents, attaching KBs or memory, writing system instructions, selecting models, or setting up RAG pipelines. Do NOT use for debugging existing agents (use analyze-trace-failures) or comparing agents across frameworks (use compare-agents).
Build, scaffold, extend, deploy, and troubleshoot event-driven AI agents and scheduled serverless agent apps on Azure Functions using azurefunctions-agents-runtime. Use when the user wants a scheduled agent, morning briefing, daily digest, timer agent, inbox summary, email or Teams briefing, background AI workflow, connector-triggered agent, event-driven AI automation, HTTP/chat agent, webhook-style agent, or Azure Functions hosted agent. Covers .agent.md, agents.config.yaml, Foundry gpt-4.1/gpt-5.x model choice, dynamic sessions for code execution and web browsing, built-in chat/API/MCP endpoints, remote MCP servers, Connector Namespaces, Office 365 or Teams MCP tools/triggers, custom Python tools, Agent Skills, azd deployment, local.settings.json, Application Insights, local development, and troubleshooting.
Build an AI agent backend with persistent memory: one Rivet Actor per conversation, queued message handling, and streaming LLM responses as realtime events.
This skill provides guidance for creating agents and applications with the GitHub Copilot SDK. It should be used when the user wants to create, modify, or work on software that uses the GitHub Copilot SDK in TypeScript, Python, Go, or .NET. The skill covers SDK usage patterns, CLI configuration, custom tools, MCP servers, and custom agents.
AI SDK 6 Beta overview, agents, tool approval, Groq (Llama), and Vercel AI Gateway. Key breaking changes from v5 and new patterns.
Comprehensive guide for developing Letta agents, including architecture selection, memory design, model selection, and tool configuration. Use when building or troubleshooting Letta agents.
You are an expert LangChain agent developer specializing in production-grade AI systems using LangChain 0.1+ and LangGraph.
Amazon Bedrock AgentCore Memory for persistent agent knowledge across sessions. Episodic memory for learning from interactions, short-term for session context. Use when building agents that remember user preferences, learn from conversations, or maintain context across sessions.