plotly-dashboard-skilllisted

# Plotly Dashboard Skill Create interactive dashboards with a single source of truth for UI and figure styling. ## Instructions 1. Capture audience, questions, and data constraints. 2. Pick a layout pattern and component library. Layout, typography, color, and the shared figure template are in [references/style.md](references/style.md). 3. Register the figure template once, before building any chart, so no figure is styled by hand. 4. Build the layout skeleton before callbacks. 5. Implement callbacks with clear inputs and outputs. Project structure, the data-callback-to-render-callback fan-out, and the advanced callback tools are in [references/architecture.md](references/architecture.md). 6. Optimize slow callbacks with caching, pre-aggregation, or background callbacks; the same reference covers when each applies. 7. Start from [examples/app.py](examples/app.py), the runnable app this skill tests. Copy its structure rather than writing a skeleton from scratch. ## Input Requirements - Audience and key decisions - Data sources and update cadence - Required filters and views - Deployment constraints ## Output - Dash app scaffold (layout + callbacks) - Consistent theming and figure templates - README with usage notes ## Quality Gates Run the smoke test before calling a dashboard done: ```bash uv run --script examples/app.py --smoke --latency-budget-ms 300 ``` It must return HTTP 200 with a measured pure-callback p95 inside the declared budget. Visual and interaction: