Chain-of-thought and step-by-step reasoning prompts for complex problem solving
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Chain-of-thought and step-by-step reasoning prompts for complex problem solving
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Chroma local vector database setup and operations for development and production
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CrewAI multi-agent orchestration setup for collaborative AI systems
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Execute development tasks to build features, producing code, tests, and configuration artifacts that satisfy specification requirements and comply with constitution standards.
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LangGraph checkpoint and persistence configuration for stateful workflow management
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Haystack NLP pipeline configuration for document processing and QA
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Conditional edge routing and state-based transitions for LangGraph workflows
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Autonomous research engineering — web search orchestration, source synthesis, hypothesis formation, and structured research report generation.
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Use when you have a written implementation plan to execute in a separate session with review checkpoints between batches.
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LangChain memory integration including ConversationBufferMemory, ConversationSummaryMemory, and vector-based memory
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Autonomously engage with complex coding tasks — multi-step planning, tool use, self-correction, and solution verification without human intervention.
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Use when starting any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
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Human-in-the-loop integration for LangGraph workflows with approval and intervention points
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Microsoft AutoGen multi-agent configuration for conversational AI systems
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Subgraph composition and modular workflow design for LangGraph
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Write feature specifications as requirements and user stories with acceptance criteria, focusing on business value and testable conditions.
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Apply general knowledge reasoning across diverse domains — trivia, commonsense inference, analogy, and factual question answering.
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Use when implementing any feature or bugfix, before writing implementation code. Enforces RED-GREEN-REFACTOR cycle.
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Use when implementation is complete, all tests pass, and you need to decide how to integrate the work.
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Multi-agent swarm formation and coordinated execution with topology-aware agent deployment, consensus protocols, and anti-drift enforcement.
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Guardrails AI validation framework setup for LLM applications. Implement input/output validation, safety checks, and structured output enforcement.
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Design technical architecture, select technology stack, and define implementation strategy from specifications and constitution constraints.
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HNSW vector search for pattern similarity retrieval and knowledge graph maintenance with PageRank scoring, community detection, and 3-tier memory management.
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LangSmith tracing and debugging setup for LLM applications. Configure observability, capture traces, and enable debugging for LangChain/LangGraph agents.
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