Use when implementing any feature or bugfix, before writing implementation code. Enforces RED-GREEN-REFACTOR cycle.
Skills in this repository
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Use when starting feature work that needs isolation from current workspace or before executing implementation plans.
Use when starting any conversation. Establishes how to find and use skills, requiring skill invocation before any response.
Use when about to claim work is complete, fixed, or passing, before committing or creating PRs. Evidence before assertions.
Use when you have a spec or requirements for a multi-step task, before touching code. Creates bite-sized TDD implementation plans with dependency tracking.
Use when creating new skills, editing existing skills, or verifying skills work before deployment.
Microsoft AutoGen multi-agent configuration for conversational AI systems
Chain-of-thought and step-by-step reasoning prompts for complex problem solving
Chroma local vector database setup and operations for development and production
Constitutional AI and safety guardrail prompts for aligned LLM behavior
Content moderation API integration using OpenAI Moderation, Perspective API, and others
CrewAI multi-agent orchestration setup for collaborative AI systems
Entity and fact extraction for user profiling and personalization
Few-shot example generation and optimization for improved LLM performance
Guardrails AI validation framework setup for LLM applications. Implement input/output validation, safety checks, and structured output enforcement.
Haystack NLP pipeline configuration for document processing and QA
Hugging Face transformer model fine-tuning and inference for intent classification
LangChain chain composition including SequentialChain, RouterChain, and LCEL patterns
LangChain memory integration including ConversationBufferMemory, ConversationSummaryMemory, and vector-based memory
LangChain ReAct agent implementation with tool binding for reasoning and action loops
LangChain retriever implementation with various retrieval strategies for RAG applications
LangChain tool creation and integration utilities for agent systems
LangFuse LLM observability integration for tracing, analytics, and cost tracking
LangGraph checkpoint and persistence configuration for stateful workflow management
Human-in-the-loop integration for LangGraph workflows with approval and intervention points
Conditional edge routing and state-based transitions for LangGraph workflows
LangGraph StateGraph builder with state schema design. Create stateful agent workflows with cycles, conditionals, and persistence.
Subgraph composition and modular workflow design for LangGraph
LangSmith tracing and debugging setup for LLM applications. Configure observability, capture traces, and enable debugging for LangChain/LangGraph agents.
LlamaIndex agent and query engine setup for RAG-powered agents
LLM-based zero-shot and few-shot classification for flexible intent detection
Scaffolds MCP App project structure with correct directory layout, dependencies, entry points, and framework-specific templates. Handles React (useApp hook), Vanilla JS, Vue, Svelte, Preact, and Solid.
Comprehensive verification checklists for MCP Apps. Tests with basic-host reference, validates handler-before-connect, text fallback, resource URI linking, single-file bundling, host styling, CSP, and legacy pattern detection.
Comprehensive Content Security Policy audit for MCP Apps in sandboxed iframes. Discovers all network origins, traces them to source, and generates CSP configuration for registerAppResource.
Integrates MCP App UI with host theming system. Applies host CSS variables, handles onhostcontextchanged, safe area insets, display mode detection, and fullscreen configuration.
Implements the core MCP Apps architectural pattern where a Tool declares _meta.ui.resourceUri referencing a registered Resource. Covers registerAppTool, registerAppResource, text fallback, structuredContent, and app-only helper tools.
Mem0 memory layer integration for AI agents. Implement persistent, semantic memory for long-term context retention and personalization.
Conversation summarization for memory compression and context management
Milvus distributed vector database configuration for large-scale RAG applications
NVIDIA NeMo Guardrails configuration for conversational safety and control