langchain-framework
LangChain LLM application framework with chains, agents, RAG, and memory for building AI-powered applications
LangChain LLM application framework with chains, agents, RAG, and memory for building AI-powered applications
Design and implement comprehensive evaluation systems for AI agents. Use when building evals for coding agents, conversational agents, research agents, or computer-use agents. Covers grader types, benchmarks, 8-step roadmap, and production integration.
Break LLM name defaults with external entropy. Use when character names cluster around statistical medians (Chen, Patel, Maya, Marcus), when cast has collision risks, or when fantasy cultures need phonologically consistent naming.
Build real-time voice AI applications using Azure AI Voice Live SDK (azure-ai-voicelive). Use this skill when creating Python applications that need real-time bidirectional audio communication with Azure AI, including voice assistants, voice-enabled chatbots, real-time speech-to-speech translation, voice-driven avatars, or any WebSocket-based audio streaming with AI models. Supports Server VAD (Voice Activity Detection), turn-based conversation, function calling, MCP tools, avatar integration, and transcription.
Use when building any system that involves AI/model calls - integrates with brainstorming, planning, and TDD to ensure model agency over hardcoded rules
Telegram bot production management, monitoring, and troubleshooting. Use when user mentions telegram bot, claude-orchestrator, bot status, bot restart, or bot monitoring.
Update AGENTS.md with new rules to prevent AI misbehavior or add operational guidelines. Use when the user says "update AGENTS.md", "add this rule", "change AI behavior", or "don't do X automatically".
Clean code patterns for Azure AI Search Python SDK (azure-search-documents). Use when building search applications, creating/managing indexes, implementing agentic retrieval with knowledge bases, or working with vector/hybrid search. Covers SearchClient, SearchIndexClient, SearchIndexerClient, and KnowledgeBaseRetrievalClient.
Creates new Agent Skills (SKILL.md + optional scripts/references) that follow the Agent Skills spec. Use when the user asks to create, structure, validate, or improve an agent skill.
Best practices for using the Council MCP server in Tzurot v3 development - When to consult external AI, how to structure prompts, model selection, and multi-turn conversations. Use when planning major changes or needing a second opinion.
Design principles for ultrathink multi-agent workflows using the Ralph Wiggum technique. Use when orchestrating multiple AI agents (Opus/Sonnet/Gemini/Codex) for complex autonomous development tasks with extended thinking and iterative improvement loops.
Create and configure Claude Code subagents for specialized task delegation. Use when defining expert AI assistants with focused responsibilities, custom prompts, and specific tool permissions.
Search rad-mem's persistent cross-session memory database. Use when user asks "did we already solve this?", "how did we do X last time?", or needs work from previous sessions.
Generate ROS 2 custom message (.msg) and service (.srv) interface definitions for educational content. This skill should be used when creating lessons that teach interface design, writing exercises involving custom data types, or generating worked examples for robotics communication protocols.
Get current Claude Code session UUID and registry info. TRIGGERS - current session, session uuid, session id, what session, which session.
Routes to appropriate PyTorch specialist skill based on symptoms and problem type
Official Anthropic SDK for Claude AI with chat, streaming, function calling, and vision capabilities
AI session compression techniques for managing multi-turn conversations efficiently through summarization, embedding-based retrieval, and intelligent context management.
Build comprehensive randomization lists for creative entropy. Use when you need to create or expand lists of story elements (professions, locations, objects, names, etc.) for use with entropy tools. Leverages research sources like Kiwix/Wikipedia to build lists with good variety and size.
Configure Ralph loop guidance via AUQ flows - forbidden/encouraged items from constraint scan. TRIGGERS - session guidance, loop configuration, /ralph:start Step 1.6.
Integrate OpenAI ChatKit framework with custom backend and AI agents. Handles ChatKit server implementation, React component integration, context injection, and conversation persistence.
Build new agent skills. Use when creating diagnostic frameworks, CLI tools, or data-driven generators that follow the established skill patterns.