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Documentation Index

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UserFeedbackTools exposes a single ask_user tool. The agent presents structured questions with predefined options (single or multi-select), the run pauses, and execution resumes once the user provides their selections. This is a human-in-the-loop pattern for clarifying intent mid-run.

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Example

cookbook/02_agents/10_human_in_the_loop/user_feedback.py
from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIResponses
from agno.tools.user_feedback import UserFeedbackTools

agent = Agent(
    model=OpenAIResponses(id="gpt-5.4"),
    tools=[UserFeedbackTools()],
    instructions=[
        "You are a helpful travel assistant.",
        "When the user asks you to plan a trip, use the ask_user tool to clarify their preferences.",
    ],
    db=SqliteDb(db_file="tmp/user_feedback.db"),
    markdown=True,
)

run_response = agent.run("Help me plan a vacation")

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Resolving the Pause

When the agent calls ask_user, the run pauses with a user_feedback_schema. Collect the user’s selections and continue the run: 
while run_response.is_paused:
    for requirement in run_response.active_requirements:
        if requirement.needs_user_feedback:
            selections = {}
            for question in requirement.user_feedback_schema:
                # present question.header, question.question, question.options
                # collect selected option labels (multi if question.multi_select)
                selections[question.question] = [...]
            requirement.provide_user_feedback(selections)

    run_response = agent.continue_run(
        run_id=run_response.run_id,
        requirements=run_response.requirements,
    )

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Question Schema

ask_user accepts a list of AskUserQuestion objects:
FieldTypeDescription
questionstrThe question. Must end with a question mark.
headerstrShort label (max 12 chars), e.g. "Destination".
optionsList[AskUserOption]2-4 options to choose from.
multi_selectboolIf True, the user can select multiple options.
Each AskUserOption has a label (1-5 words) and an optional description.

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Toolkit Params

ParameterTypeDefaultDescription
instructionsOptional[str]defaultsOverride the default LLM instructions.
add_instructionsboolTrueAdd the instructions to the agent’s system message.

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Developer Resources