infographic-and-data-viz
FeaturedThe craft of turning real data into honest, scannable, shareable infographics and charts. Use when someone wants to visualize data, make an infographic, build a chart/graph, turn a finding or stat into a visual, or fix a chart that's confusing or misleading. A great data viz makes one insight land in 3 seconds. Uses the CHART framework (chart choice, headline takeaway, honest scale, reduce to signal, tag source + accessibility). Reads brand-profile + design-and-templates first and pulls real data from data-and-original-research / analytics-and-reporting. The agent designs the spec; a design/chart tool renders it; the human approves; WoopSocial publishes the image (it does not generate media). NEVER distorts scales or fabricates a data point/source; cites source + date; accessibility required. Distinct from design-and-templates (brand design), quote-cards-and-text-graphics (a lone quote/number), data-and-original-research (originates the data), and analytics-and-reporting.
Install
Quality Score: 89/100
Skill Content
Details
- Author
- social-media-skills
- Repository
- social-media-skills/skills
- Created
- 2 months ago
- Last Updated
- yesterday
- Language
- Shell
- License
- MIT
Similar Skills
Semantically similar based on skill content — not just same category
honest-dataviz
Charts and dashboards that read at a glance, survive a colour-blind reviewer, and never imply more certainty than the data has. Use this BEFORE writing any chart, graph, KPI tile, dashboard, or data visualization — in any library or in hand-drawn SVG/HTML — and whenever choosing chart colours, building a stat row, or deciding whether something should be a chart at all.
dataviz
Design data visualizations - charts, graphs, plots, and dashboards - that are correct, legible, and honest, in any medium. Consult this BEFORE writing any chart, graph, plot, or dashboard code, whatever the library (matplotlib, plotly, d3, Recharts, inline SVG) or output (static image, notebook, web app, deck). Use whenever a task involves picking a chart type, a color palette for data, dashboard or KPI-tile layout, axis and label formatting, or making a visualization colorblind-safe and light/dark-ready. Covers the data-shape to mark-type heuristic, chart anti-patterns to refuse (pie overuse, dual axes, truncated bar axes, rainbow scales, 3D), a brand-neutral colorblind-safe palette you can rebrand, composition, interaction and static degradation, and a final validation checklist. Data charts only - structural diagrams and deck theming are out of scope.
dataviz
Design and implement evidence-first charts from real data for technical blogs, reports, READMEs, and product explainers. Use when asked for a benchmark graph, data illustration, performance chart, tradeoff plot, small multiple, or an editorial chart in React/Recharts or a static plotting stack. Do NOT use for text-only diagrams (use show-me), hand-drawn conceptual art (use sketch-concept), or dashboard UI design.