数据与研究

data-storytelling

wshobson/agents

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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安装命令

npx skills add https://github.com/wshobson/agents --skill data-storytelling

要点

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

  • Three-pillar framework combining data evidence, narrative meaning, and visual clarity to structure insights for maximum impact
  • Includes five story templates (Problem-Solution, Trend, Comparison, Executive Summary, One-Page Dashboard) with ready-to-use structures for common business scenarios
  • Progressive reveal and annotation techniques to layer complexity, build understanding, and highlight key inflection points
  • Writing guidance covering headline formulas, transition phrases, and strategies for handling uncertainty and presenting ranges

SKILL.md

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