monitoring-dashboard

To generate a Marimo dashboard, provide your structured CSV or JSON project data to the skill, which automatically loads the data, renders Plotly charts, and outputs a runnable dashboard.py file for visualizing progress and test results.

Yes, you can visualize test results and requirements traceability either together in a single integrated view or as separate dashboards, depending on your project monitoring needs and parameter-driven customizations.

Automating project progress reporting is best handled by generating dynamic Marimo notebooks that visualize sprint progress and QA test results directly from your structured data, providing updated integrated views for release cycles.

Yes, you need pandas and plotly installed in your Python environment, as the skill uses these libraries for data loading and chart rendering within the generated Marimo notebooks.

Automated dashboard generation works by loading your JSON or CSV structured data, applying parameter-driven customizations, and using Python libraries to render charts and produce an interactive Marimo notebook file.

The skill's dashboard generation requires structured JSON or CSV data to map requirements traceability, meaning unstructured or poorly formatted project data will not render correctly into the Marimo notebook views.