when-chaining-agent-pipelines-use-stream-chain
Chain agent outputs as inputs in sequential or parallel pipelines for data flow orchestration
Chain agent outputs as inputs in sequential or parallel pipelines for data flow orchestration
Process and transform arrays of data with common operations like filtering, mapping, and aggregation
Validate data against schemas, business rules, and data quality standards.
Optimize AgentDB vector search performance using quantization for 4-32x memory reduction, HNSW indexing for 150x faster search, caching, and batch operations for scaling to millions of vectors.
AI Runtime分层记忆系统,支持SQL风格的事件查询、时间线管理,以及记忆的智能固化和检索,用于项目历史追踪和经验传承
Standardized tool set definitions for Claude Code agents ensuring consistent tool access across similar agent types
Use when the user asks to describe, summarize, analyze, compare, explain, or report on something (text, data, events, systems) without asking for recommendations or next steps.
Use when working with Quetrex's voice interface, OpenAI Realtime API, WebRTC, or echo cancellation. Knows Quetrex's specific voice architecture decisions and patterns. CRITICAL - prevents breaking working voice system.
Guide for creating new Agent Skills. Use this skill when you need to create a new skill.
Enterprise-grade PowerPoint deck generation using evidence-based prompting, workflow enforcement, constraint-based design
Build evaluation frameworks for agent systems. Use when testing agent performance, validating context engineering choices, or measuring improvements over time.
Build AI chat interfaces with custom backends, authentication, and context injection. Use when integrating chat UI with AI agents, adding auth to chat, injecting user/page context, or implementing httpOnly cookie proxies. Covers ChatKitServer, useChatKit, and MCP auth patterns. NOT when building simple chatbots without persistence or custom agent integration.
Use when facing 3+ independent failures that can be investigated without shared state or dependencies. Dispatches multiple Claude agents to investigate and fix independent problems concurrently.
Guide for creating MCP (Model Context Protocol) servers. Use this when building integrations with external services, creating new MCP servers, or connecting Claude to APIs.
This skill is a practical, 'use-it-while-debugging' reference for getting a LiveKit + Letta voice agent working reliably.
Domain knowledge for Physical AI, ROS 2, and Humanoid Robotics.
Use when integrating Context7 (knowledge/context store) for document ingestion, semantic search, or scoped context retrieval. Triggers for: uploading documents, searching knowledge base, filtering by role/tenant, or providing AI with document-grounded context. NOT for: general database queries, file storage without context semantics, or non-document content.
Meta-skill for creating production-ready Claude Code skills using evaluation-driven development, progressive disclosure patterns, comprehensive validation, and two-Claude iterative methodology
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
Details of the RAG Chatbot, including UI and backend logic.
Context tracking and decision logging patterns for intentional memory management in Claude Code Waypoint Plugin. Use when you need to remember user preferences, track decisions, capture context across sessions, learn from corrections, or maintain project-specific knowledge. Covers when to persist context, how to track decisions, context boundaries, storage mechanisms, and memory refresh strategies.
Automatically activated when user asks to "find patterns in...", "identify repeated code...", "analyze the architecture...", "what design patterns are used...", or needs to understand code organization, recurring structures, or architectural decisions