Agent skill · writing content · wshobson
data-storytelling
Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.
Why this skill is useful
Provides structured frameworks and best practices for transforming data into compelling narratives that the AI wouldn't reliably generate on its own.
What it needs
About 1k tokens when loaded. Last updated 2026-08-05. 38,570 stars on the source repository.
What this skill does
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 2. Narrative Arc 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
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills wshobson/data-storytelling