deep agents core
Configure a Deep Agents application around its harness and supported extension points.
Discover useful agent workflows. Compare source quality, maintenance, licenses and review signals before you install.
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Configure a Deep Agents application around its harness and supported extension points.
Choose Deep Agents storage backends according to persistence and filesystem requirements.
Coordinate Deep Agents tasks with explicit delegation, planning and approval boundaries.
Choose between LangChain, LangGraph and Deep Agents from the required control model.
Design agent evaluations around reviewed tasks, controlled environments and explicit verifiers.
Select framework and provider packages that match the intended LangChain application.
Build a LangChain agent with explicit tools, middleware and output expectations.
Control agent execution through middleware hooks and real approval interruptions.
Assemble a retrieval pipeline with explicit document, chunk, embedding and storage choices.
Use LangGraph CLI commands with clear distinctions between local development and deployment.
Evaluate specialized decision models for bounded graph-routing choices.
Represent an agent workflow through explicit graph state, nodes and transitions.
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Move from a deliberate design direction to a performance review and a browser check of the real user journey.
4 skills · explore kit ↗Build a clear chain from a reproduced defect to a meaningful regression test and fresh completion evidence.
3 skills · explore kit ↗Connect implementation planning, PostgreSQL review and deployment evidence for a service with persistent data.
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