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storytelling-viz

Transform raw datasets into interactive Plotly visualizations with a single takeaway.

21|3|Updated Apr 12, 2026
Search Tags:#data visualization#data storytelling#data validation#plotly#visual QA#chart design#stakeholder reporting
One-click install
npx skills add https://github.com/yudong-94/storytelling-viz-skill --skill storytelling-viz
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: storytelling-viz
Source: https://github.com/yudong-94/storytelling-viz-skill/tree/main
Command: npx skills add https://github.com/yudong-94/storytelling-viz-skill --skill storytelling-viz

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill eliminates the guesswork and manual effort of turning raw datasets into clear, stakeholder-ready interactive visualizations. It ensures your chart has a single defensible takeaway, stays honest to the underlying data, and includes all necessary context and caveats, without requiring you to handle website publishing or dashboard development.

Core Features & Use Cases

  • Dataset Validation & Chart Recommendation: Automatically inspects datasets to verify sources, check comparability, and recommend one default chart plus one fallback tailored to your data's story.
  • Stakeholder-Ready Artifacts: Produces self-contained index.html and preview.html files, plus 2-3 insight bullets and explicit source citations, ready for local review or embedding.
  • Built-In Quality Guardrails: Enforces non-negotiable honesty, intuition, and concision tests, requires user confirmation before building when multiple chart directions are plausible, and includes rendered visual QA to catch clipping, overlap, or spacing issues.
  • Use Cases: Ideal for analyst-to-stakeholder charts, one-off story visualizations, visual explainers for reports or presentations, and example galleries for chart-generation workflows. It works portably in both Codex and Claude Code environments.

Quick Start

Use the storytelling-viz skill to inspect my attached dataset, recommend the best chart and one fallback, wait for my confirmation, then build a polished Plotly visualization with index.html and preview.html.

Frequently Asked Questions about storytelling-viz

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

FAQPage Schema
How do I turn raw data into interactive Plotly visualizations for stakeholder reporting?▼

To create interactive Plotly visualizations, use a story-first approach that validates your dataset, recommends a chart, and outputs self-contained HTML files with insight bullets. This ensures a single defensible takeaway for stakeholder reporting.

What is data storytelling and how does it improve chart design?▼

Data storytelling improves chart design by enforcing dataset source verification and visual QA, ensuring your visualization has a clear, defensible takeaway. This approach prevents clipping or overlap issues and outputs polished, interactive visual explainers.

Can I generate a fallback chart option when building one-off story visualizations?▼

Yes, you can generate a fallback chart option for one-off story visualizations. The workflow inspects your dataset to recommend one default chart plus one fallback, requiring your confirmation before building the final interactive Plotly output.

Does the storytelling visualization process work without external dashboard development tools?▼

Yes, the storytelling visualization process works without external dashboard development tools. It produces self-contained local review artifacts, including index.html and preview.html files, which can be embedded directly without requiring extra publishing setup.

What are the limitations of automated chart recommendation for visual explainers?▼

A limitation of automated chart recommendation is that when multiple chart directions are plausible, it requires user confirmation before building. Additionally, built-in data honesty checks and rendered visual QA must pass to prevent clipping or overlap issues.

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