visualize-data

Applies a token-based palette and restraint checklist to charts built with the dataviz skill.

1|Updated Jul 13, 2026
One-click install
npx skills add https://github.com/dineshrevunuru/SuperSkills --skill visualize-data-dineshrevunuru
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: visualize-data
Source: https://github.com/dineshrevunuru/SuperSkills/tree/main/visualize-data
Command: npx skills add https://github.com/dineshrevunuru/SuperSkills --skill visualize-data-dineshrevunuru

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Charts often ship with rainbow palettes, cluttered legends and gridlines, and topic-only titles that hide the finding. This Skill layers a consistent design register over the built-in dataviz method so every chart, dashboard, or stat tile follows one palette source and one restraint standard. ## Core Features & Use Cases - Palette swap discipline: Replaces dataviz's placeholder palette with tokens from build-token-system or apply-personal-brand, then re-runs the color validator on the swapped palette. - Restraint pass checklist: Enforces one finding per chart, direct labeling over legends, cut-or-aggregate for too many series, and motion rules honoring reduced-motion. - Escalation decision tree: Routes data querying to data plugins, significance claims to use-quantitative-evidence, and dashboard scaffolding to data:build-dashboard. - Use Case: When asked to chart usability test completion rates by task, it produces a bar chart where the failing task carries the single accent color, other bars drop to neutral tints, and the title states the finding instead of the topic. ## Quick Start Chart the usability test completion rates by task using the visualize-data approach with a finding-first title and single accent color.

Frequently Asked Questions about visualize-data

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I make charts follow a consistent design system palette?

Invoke the built-in dataviz skill first for chart form and mark specs, then swap its placeholder palette for tokens from build-token-system or apply-personal-brand. Re-run dataviz's color validator on the swapped palette before shipping.

What chart type should I use for categorical comparisons?

The dataviz skill's form heuristic decides chart type based on data shape; for categorical comparisons with few items it selects a bar chart. This skill never overrides that decision, it only layers palette and restraint on top.

Can I use this skill with matplotlib, plotly, or Recharts?

Yes, the method applies to any medium including matplotlib, plotly, Recharts, d3, inline SVG, HTML artifacts, and exported PNG. The palette swap and restraint pass work identically regardless of rendering library.

When should I not use this chart visualization skill?

Do not use it for computing, joining, or querying data, which belongs to data plugins, or for judging whether numbers support a claim, which belongs to use-quantitative-evidence. It only handles presentation of already-prepared data.

How do I handle charts with too many data series?

Cut or aggregate the series, such as showing the top five plus an other category, rather than thinning lines or shrinking fonts. The restraint pass explicitly forbids shrinking to fit more series.