Proact0

architecting-act

Designs Act and Cast architectures through dynamic questioning, outputting validated CLAUDE.md with mermaid diagrams. Covers resilience patterns (Saga/compensation, long-running threads with DeltaChannel, graceful drain checkpoints, node timeout boundaries) from langgraph v1.2+. Use when starting new Act project, adding cast, planning architecture, extracting sub-cast (10+ nodes), redesigning existing cast, or ask "design architecture", "plan cast", "redesign cast", "create CLAUDE.md".

developing-cast

Implements LangGraph cast components following systematic workflow (state, deps, nodes, conditions, graph). Use when implementing cast, building nodes/agents/tools, need LangGraph patterns (memory, retry, guardrails, vector stores, node timeouts, error handlers, DeltaChannel, graceful shutdown), or ask "implement cast", "build graph", "add node".

developing-deepagent

Implements DeepAgent components using LangChain's deepagents SDK. Use when building deep agents with create_deep_agent, configuring backends/subagents/skills/memory/interpreter, need DeepAgent patterns (sandbox, HITL interrupts, long-term memory, subagent spawning, subagent structured output, QuickJS code interpreter with programmatic tool calling), or ask "implement deep agent", "add subagent", "configure backend", "add interpreter".

streaming-cast

Implements LangGraph v3 event streaming for graphs with subgraphs and agents. Use when adding streaming to runtime/API endpoint, need token streaming, custom stream projections, subagent streaming, or ask "add streaming", "stream tokens", "stream graph".

Testing & QA Solid

testing-cast

Guides pytest test writing for LangGraph casts with mocking patterns for LLM/API/Store calls. Use when writing tests, need mock strategies, setting up fixtures, testing nodes/graphs (v3 event streaming, timeouts, error handlers, graceful shutdown), or ask "write tests", "mock LLM", "test coverage".