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Analysis & spreadsheets41k · #4818

data-storytelling

Makes your agent turn data into easy-to-understand stories. It's useful for presenting complex information clearly and persuasively.

What it does

This tool turns raw data into interesting stories to help make decisions. It uses structure, context, and visuals to make numbers easy to understand.

When to use it

  • ✓When presenting analytics to bosses.
  • ✓When creating quarterly business reports.
  • ✓When making presentations for investors.

Example of what to ask your AI

“Turn this sales data into a presentation for investors.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/wshobson/agents/blob/main/plugins/business-analytics/skills/data-storytelling/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/wshobson/agents/blob/main/plugins/business-analytics/skills/data-storytelling/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

The tool organizes your data into a story structure with a beginning, middle, and end. It uses charts and simple explanations to show what the numbers mean and what to do next.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add wshobson/agents --skill data-storytelling

Or download just the file:

curl -L https://raw.githubusercontent.com/wshobson/agents/main/plugins/business-analytics/skills/data-storytelling/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

Data Storytelling

Transform raw data into compelling narratives that drive decisions and inspire action.

When to Use This Skill

  • Presenting analytics to executives
  • Creating quarterly business reviews
  • Building investor presentations
  • Writing data-driven reports
  • Communicating insights to non-technical audiences
  • Making recommendations based on data

Core Concepts

1. Story Structure

Setup → Conflict → Resolution

Setup: Context and baseline
Conflict: The problem or opportunity
Resolution: Insights and recommendations

2. Narrative Arc

1. Hook: Grab attention with surprising insight
2. Context: Establish the baseline
3. Rising Action: Build through data points
4. Climax: The key insight
5. Resolution: Recommendations
6. Call to Action: Next steps

3. Three Pillars

Pillar Purpose Components
Data Evidence Numbers, trends, comparisons
Narrative Meaning Context, causation, implications
Visuals Clarity Charts, diagrams, highlights

Detailed patterns and worked examples

Detailed pattern documentation lives in references/details.md. Read that file when the navigation tier above is insufficient.

Best Practices

Do's

  • Start with the "so what" - Lead with insight
  • Use the rule of three - Three points, three comparisons
  • Show, don't tell - Let data speak
  • Make it personal - Connect to audience goals
  • End with action - Clear next steps

Don'ts

  • Don't data dump - Curate ruthlessly
  • Don't bury the insight - Front-load key findings
  • Don't use jargon - Match audience vocabulary
  • Don't show methodology first - Context, then method
  • Don't forget the narrative - Numbers need meaning
FAQ

What is 'Setup → Conflict → Resolution'?

It's a way to tell a story: 'Setup' is the initial context, 'Conflict' is the problem or opportunity, and 'Resolution' are the solutions and conclusions.

What are the 'Three Pillars'?

These are the essential elements: Data (the numbers), Narrative (the meaning), and Visuals (the charts) to tell the story.

What does 'Don't data dump' mean?

It means not showing all the data at once. Choose only the most important data for your story.

Details

Original description by the author

Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.

repo: wshobson/agents

Popularity

GitHub stars
41k
Ranking position
#4818
License
MIT
Updated
10/15/2026

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