# Data Storytelling

> Data narrative design, chart annotation, and turning numbers into compelling stories.

- Skill: `dragoon0x/data-storytelling` (Agent Skill)
- Install (CLI): `npx skillmds@latest add dragoon0x/data-storytelling`
- Raw SKILL.md: https://api.skillmd.com/api/skills/dragoon0x/data-storytelling/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: dragoon0x (https://skillmd.com/u/dragoon0x)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/dragoon0x/data-storytelling

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# Data Storytelling

## Data Narrative Principles

1. **Lead with the insight, not the data.** "Sales doubled in Q3" before showing the chart.
2. **One story per chart.** If a chart tells two stories, make two charts.
3. **Annotate the interesting parts.** Labels on peaks, dips, and inflection points.
4. **Provide context.** "42% increase" compared to what? Industry average? Last year? Goal?
5. **Design for the audience.** Executives want conclusions. Analysts want data.

## Chart Annotation
- Callout labels on data points that matter.
- Reference lines for targets/goals/averages.
- Shaded regions for time periods of interest.
- Brief text annotations explaining anomalies.

## Presentation Order
1. **Headline:** The conclusion in one sentence.
2. **Chart:** Visual evidence.
3. **Context:** Comparison, trend, benchmark.
4. **Implication:** What this means for the business.
5. **Action:** What to do about it.