data-storytelling

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

AI & Automation 36,166 stars 3920 forks Updated yesterday MIT

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Skill Content

# 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 - *...

Details

Author
wshobson
Repository
wshobson/agents
Created
10 months ago
Last Updated
yesterday
Language
Python
License
MIT

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