agent-framework/python/samples/02-agents/skills/script_approval

Script Approval — Human-in-the-Loop for Skill Scripts

This sample demonstrates how to require human approval before executing skill scripts using the require_script_approval=True option on SkillsProvider.

How It Works

When require_script_approval=True is set, the agent pauses before executing any skill script and returns approval requests instead:

1. The agent tries to call run_skill_script — execution is paused
2. result.user_input_requests contains approval request(s) with function name and arguments
3. The application inspects each request and decides to approve or reject
4. request.to_function_approval_response(approved=True|False) creates the response
5. The response is sent back via agent.run(approval_response, session=session)
6. If approved, the script executes; if rejected, the agent receives an error

Key Components

• require_script_approval=True — Gates all script execution on human approval
• result.user_input_requests — Contains pending approval requests after agent.run()
• request.to_function_approval_response() — Creates an approval or rejection response

Running the Sample

Prerequisites

• An Azure AI Foundry project with a deployed model (e.g. gpt-4o-mini)

Environment Variables

Set the required environment variables in a .env file (see python/.env.example):

• FOUNDRY_PROJECT_ENDPOINT: Your Azure AI Foundry project endpoint
• AZURE_OPENAI_DEPLOYMENT_NAME: The name of your model deployment (defaults to gpt-4o-mini)

Authentication

This sample uses AzureCliCredential for authentication. Run az login in your terminal before running the sample.

Run

cd python
uv run samples/02-agents/skills/script_approval/script_approval.py

Learn More

• File-Based Skills Sample
• Code-Defined Skills Sample
• Mixed Skills Sample
• Agent Skills Specification