> **data-storytelling** — skill 27 of 183 in [wshobson/agents](https://skillsdocs.com/wshobson/agents).
>
> Book (all skills, one file): https://skillsdocs.com/wshobson/agents.md
> Machine manifest: https://skillsdocs.com/wshobson/agents/.well-known/agent-skills/index.json
> Install the book: `npx skills add wshobson/agents`
> Upstream: https://github.com/wshobson/agents/blob/main/plugins/business-analytics/skills/data-storytelling/SKILL.md @ `main`
> Raw bytes, no header: https://raw.githubusercontent.com/wshobson/agents/main/plugins/business-analytics/skills/data-storytelling/SKILL.md
> Base for relative paths: https://raw.githubusercontent.com/wshobson/agents/main/plugins/business-analytics/skills/data-storytelling/
> Licence: MIT — https://spdx.org/licenses/MIT.html
>
> Bundled files (1), referenced from this skill's directory:
>   - `references/details.md` — https://raw.githubusercontent.com/wshobson/agents/main/plugins/business-analytics/skills/data-storytelling/references/details.md
>
> Content © its authors, served unmodified. Takedown: https://github.com/DreambaseAI/skillsdocs/issues/new?labels=takedown&title=Takedown+request

<!-- Verbatim upstream SKILL.md follows, YAML frontmatter included. -->

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

# 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