# 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.

Source: https://skillsagentes.com/skills/wshobson/agents/data-storytelling
Repository: https://github.com/wshobson/agents
Author: wshobson
License: MIT
Updated: hace 2 meses
Context cost: 51 tok installed, 530 tok once triggered, 3.1k tok with every bundled file
Bundle: 2 files, 12 KB
Permissions requested: none declared

## Install

```bash
npx -y skills add wshobson/agents --skill data-storytelling --agent claude-code
```

## What it does

- Estructura datos crudos en narrativas con arco de setup-conflicto-resolución
- Aplica un gancho, contexto, clímax e insight clave con llamada a la acción
- Combina datos, narrativa y visuales como los tres pilares de la historia
- Da reglas de qué hacer y qué evitar al presentar hallazgos a audiencias

## Use it when

- Presentar analíticas a ejecutivos
- Crear revisiones trimestrales de negocio (QBRs)
- Construir presentaciones para inversores
- Comunicar insights a audiencias no técnicas o hacer recomendaciones basadas en datos

## What triggers it

- "Ayúdame a convertir estos datos en una presentación para el equipo ejecutivo"
- "Necesito estructurar el reporte trimestral de negocio con una narrativa clara"
- "Quiero presentar estos insights a inversores de forma persuasiva"

## Files

- SKILL.md — 2 KB
- references/details.md — 10 KB

## SKILL.md

Reproduced verbatim from wshobson/agents under MIT. This section is the upstream document and is in English.

# 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

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Skills Agentes — https://skillsagentes.com/skills/wshobson/agents/data-storytelling