What problem does it solve?
The Data Visualization Crit helps product teams avoid misleading or unclear charts by evaluating chart selection, data encoding, dashboard composition, and annotation so quantitative information is communicated accurately and accessibly.
Core Features & Use Cases
- Chart selection framework that maps data relationships (comparison, trend, distribution, correlation, etc.) to appropriate chart types and flags anti-patterns.
- Encoding and annotation guidance that prioritizes perceptual accuracy (position, length) and enforces labeling, reference lines, and accessibility constraints.
- Dashboard composition and interaction patterns including hero/supporting hierarchy, cross-filtering affordances, and static fallbacks for non-interactive contexts.
- Iterative critique workflow that reads .design-crit/state.json and prior locked facets, generates 2–4 HTML wireframe options with realistic mock data, accepts feedback rounds, and produces a locked option with implementation tokens.
Quick Start
Generate three distinct dashboard visualization options for the brief in .design-crit/brief.md and produce a compare view with chart inventory and recommendations.
