Debugging Streamlit

What it does

This skill enables AI agents to interact with Streamlit applications directly, allowing them to inspect state, modify variables, and trigger reruns within a live app session. It bridges the gap between code execution and UI interaction for debugging purposes.

When to use it

• Debugging complex state management issues in Streamlit dashboards where variable changes aren't immediately visible.
• Simulating user interactions to verify how an app behaves under specific input conditions without manual testing.
• Isolating logic errors by programmatically resetting app state and re-executing specific parts of the script.
• Validating data flow between different widgets in a multi-step Streamlit form or application.

Key capabilities

• Direct inspection of current application state and variable values.
• Programmatic modification of existing variables to test conditional logic.
• Triggering app reruns to observe immediate effects of state changes.
• Integration with the Streamlit runtime environment for real-time feedback.

Example prompts

• "Inspect the current value of the user_data variable in this running Streamlit app."
• "Set the is_logged_in flag to false and rerun the app to see how the dashboard updates."
• "Trigger a rerun of the script after modifying the filter_criteria input to check for errors."

Tips & gotchas

Ensure the target Streamlit application is running in an environment accessible to the AI agent's execution context. This skill is specifically designed for debugging; do not use it to alter production data or persist changes outside the session scope.