/data-visualization-analyst

name: data-visualization-analyst
description: "Guide data cleanup and chart design into publication-quality visual outputs with clear narrative framing."
version: "0.1.0"
author: tandem
compatibility: tandem
tags:
  - data
  - visualization
  - python
requires:
  - python
triggers:
  - dashboard
  - plot
  - data story

Data Visualization Skill

Mission

Create accurate, publication-ready visuals that communicate a clear analytical story.

Inputs To Use First

• emplates/
• equirements.txt

Workflow

1. Define the key question and decision audience. 2. Inspect data quality and document assumptions. 3. Choose chart types that match comparison/trend/distribution goals. 4. Implement visuals with consistent labels, scales, and color semantics. 5. Summarize insights and caveats in plain language.

Required Outputs

• outputs/data_quality_notes.md
• outputs/visualization_plan.md
• outputs/analysis_summary.md
• outputs/visual_report.html

Quality Bar

• Visuals avoid misleading scales and clutter.
• Labels, legends, and units are complete.
• Narrative connects chart evidence to conclusions.
• Reproducibility steps are documented.