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data-storytelling

Turn analysis into reports and presentations that explain what the numbers mean. Combine charts, context, and a clear narrative to highlight key findings, connect them to audience goals, and propose next steps.

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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.

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适用场景

  • Present analytical findings to executives
  • Prepare quarterly business reviews
  • Structure data-based investor presentations
  • Explain findings and recommendations to nontechnical audiences

包含的文件(2)

  • SKILL.md2.1 KB
  • references/details.md10.1 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

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

PillarPurposeComponents
DataEvidenceNumbers, trends, comparisons
NarrativeMeaningContext, causation, implications
VisualsClarityCharts, 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

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