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Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
Fetch and explain Claude Code changelog for specific versions. Use when users ask about Claude Code updates, version changes, new features, bug fixes, or want to understand what changed between versions. Triggers on queries like "What's new in Claude Code X.Y.Z?", "Claude Code changelog", "What changed in the latest version?", or "Explain Claude Code updates".
End-to-end automated daily competition workflow. Orchestrates scrape, analyze, compose, and notify skills - all unattended for cron execution.
Build Claude agents using TypeScript with the @anthropic-ai/claude-agent-sdk. Use this skill when implementing conversational agents, building tools for agents, setting up streaming responses, or debugging agent implementations. Covers the tool wrapping pattern, SDK initialization, agent architecture, and best practices.
Create new specialized agent. Use when user wants reusable agent for repetitive pattern. Examples: code-reviewer, linter, doc-generator.
Creates and configures stdio Model Context Protocol (MCP) server connections for OpenAI Agents SDK
Enables Claude to interact with Gemini AI chat for quick queries, brainstorming, and alternative AI perspectives
Gemini CLI is a command-line interface tool that provides direct access to Google's Gemini AI models through the terminal, designed specifically for developers and technical professionals. It serves a...
Scaffold development rules for AI coding agents. Auto-invoked when user asks about setting up rules, coding conventions, or configuring their AI agent environment.
Builds voice-enabled CLI todo applications with speech-to-text input, keyword parsing, and persistent JSON storage. Use when creating or extending CLI todo apps with voice control capabilities, or when working with SpeechRecognition and command parsing.
Initialize the memory system in an AI-ready vault. Creates the folder structure, Memory.md dashboard, and example files needed for cross-session memory persistence. Use when setting up a new vault or adding memory capabilities to an existing vault.
Guide for creating effective skills. This skill should be used when users want to create a new skill or update an existing skill that extends Claude with specialized knowledge, workflows, or tool integrations.
Your approach to handling backend providers. Use this skill when working on files where backend providers comes into play.
Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects the agent ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) The agent realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks.
Best practices for memory architecture design including user vs agent vs session memory patterns, vector vs graph memory tradeoffs, retention strategies, and performance optimization. Use when designing memory systems, architecting AI memory layers, choosing memory types, planning retention strategies, or when user mentions memory architecture, user memory, agent memory, session memory, memory patterns, vector storage, graph memory, or Mem0 architecture.
Learn how Nexus skills work. Load when user mentions: learn skills, how do skills work, what is a skill, skill tutorial, skill structure, understand skills, explain skills, when to create skill, skill vs project. 10-12 min.
This skill should be used when the user asks to "run local LLMs", "use LM Studio", "configure local AI server", "estimate VRAM requirements", "load a model locally", or needs guidance on OpenAI-compatible local API usage, model quantization selection, GPU offload configuration, MCP server integration, or headless LLM server management. Covers local AI inference, CLI automation, SDK integration, and hardware optimization.
Guide for creating new skills in @assistantName@'s personal AI infrastructure. Use when user wants to create, update, or structure a new skill that extends capabilities with specialized knowledge, workflows, or tool integrations. Follows both Anthropic skill standards and PAI-specific patterns.
Train LangChain/LangGraph agents using Microsoft Agent-Lightning APO (Automatic Prompt Optimization). Use when user mentions APO training, prompt optimization, agent-lightning, training multi-agent systems, training single agents, or optimizing agent prompts.
