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name: agent-workflows description: "Build, configure, run, stream, serialize, load, and debug smolagents CodeAgent, ToolCallingAgent, MultiStepAgent, managed-agent, memory, planning, final-answer-check, and prompt-template workflows." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Agent Workflows

Use this sub-skill when the task is to create or debug a smolagents agent workflow: choosing CodeAgent vs ToolCallingAgent, configuring MultiStepAgent.run(), composing managed agents, enabling planning, inspecting memory, validating final answers, streaming steps, or saving/loading agents.

Route First

• Use CodeAgent when the model should write Python actions and you want stateful code execution through the Python executor.
• Use ToolCallingAgent when the model natively emits tool calls and you want JSON-like tool invocation, including parallel tool calls controlled by max_tool_threads.
• Use managed agents when a manager should delegate a subtask to a specialized CodeAgent or ToolCallingAgent; every managed agent must have name and description.
• Use run(..., return_full_result=True) or initialize with return_full_result=True when the caller needs output, token usage, timing, state, and serialized memory steps.
• Use memory, callbacks, and planning recipes in references/planning-and-memory.md for run inspection, reset=False, planning customization, or step-level intervention.

Boundaries

• For custom tools, MCP tools, Hub tools, or tool authoring, route to tools-and-integrations.
• For model classes, provider credentials, inference parameters, and local model backends, route to model-providers.
• For executor_type, remote executor setup, import authorization, and sandbox/security trade-offs, route to execution-and-safety.
• For smolagent, webagent, Gradio UI, or wrapper entry points, route to cli-and-ui.

Core References

• Start with references/api-reference.md for constructor parameters, run options, return values, and serialization APIs.
• Use references/workflows.md for concrete workflow recipes: single agents, managed agents, streaming, final-answer checks, and save/load.
• Use references/planning-and-memory.md for planning_interval, prompt template customization, callbacks, memory inspection, replay, and resume.
• Use references/troubleshooting.md for final-answer, parsing, imports, max-steps, prompt template, managed-agent, serialization, and memory issues.

Bundled Script

• scripts/inspect_agent_run.py runs a deterministic no-network CodeAgent smoke workflow with a fake model, optional streaming, full-result output, and memory summaries. Run python scripts/inspect_agent_run.py --help for options.