agents-tools-and-streaming

# Agents, Tools, and Streaming Use this sub-skill when the task involves AdalFlow agent execution, tool wrapping, tool calling, streaming run events, human approval for tools, or MCP-served tools. ## Route here for - Wrapping Python callables as `FunctionTool`, including sync, async, sync-generator, async-generator, and bound-method tools. - Inspecting or constructing `FunctionDefinition`, `Function`, `FunctionExpression`, `FunctionOutput`, or `ToolOutput` values. - Building a `ToolManager`, parsing function expressions, or executing tool calls directly. - Constructing `Agent`, `Runner`, or legacy `ReActAgent` workflows after the model client / generator setup is known. - Calling `Runner.call`, `Runner.acall`, or `Runner.astream` and consuming `RunnerResult`, step history, and stream events. - Adding human-in-the-loop approvals through `PermissionManager`, CLI/FastAPI handlers, `require_approval`, or pre-execution confirmation details. - Integrating MCP tools through MCP server parameter dataclasses, `MCPFunctionTool`, and `MCPToolManager`. ## Route elsewhere - Model client, provider credentials, `Generator`, prompt/model kwargs, and provider streaming setup belong to `model-client-and-generator-workflows`. - DataClass schemas, parser design, and general structured output repair belong to `core-components-and-structured-io` unless the schema is specifically an agent final `answer_data_type`. - Retrieval/RAG tools belong to `retrieval-rag-and-data-pipelines` before wrapping them for agent use here. - Tracing spans, logs, MLflow, and persistent observability belong to `tracing-observability-and-configuration`. - Training and optimizer behavior for agents/tools belongs to `evaluation-and-optimization`. ## Read these references 1. [references/agents-and-tools.md](references/agents-and-tools.md) for `FunctionTool`, `ToolManager`, `Agent`, `Runner`, `ReActAgent`, tool outputs, and fake-planner testing. 2. [references/streaming-and-run-results.md](references/streaming-and-run-results.md) for `RunnerResult`, `StepOutput`, streaming event types, and robust event consumption loops. 3. [references/mcp-and-permissions.md](references/mcp-and-permissions.md) for tool approval flows, permission handlers, and MCP manager/server parameter patterns. 4. [references/troubleshooting.md](references/troubleshooting.md) for unsafe tools, missing annotations, async-loop issues, result formatting, max-step exhaustion, finalization, permission denials, stream consumption, and missing MCP dependencies. ## Safe bundled checks - `python scripts/function_tool_smoke.py` verifies service-free `FunctionTool` and `ToolManager` behavior. - `python scripts/agent_runner_fake_planner_smoke.py` verifies `Agent` + `Runner` sync, async, streaming, and permission behavior with a fake planner and no provider calls. Run these only in an environment where `adalflow` is importable. They do not require API keys, network services, provider calls, or MCP servers.