Set Up a Data Visualisation Environment

Use this after skills/choose-tool has selected a library. The goal is a minimal, reproducible environment the user can iterate in.

General principles

• Reproducible by default: pin versions, commit lockfiles.
• One tool per project unless the user has asked for a composite.
• Separate data from code: raw input under data/, generated output under output/ (or dist/), source under src/.
• Headless-capable: if the target is static figures in a report, ensure the build can run without a display server.

Recipe: Python (Matplotlib / Bokeh / Plotly Dash)