Data Storytelling

Data storytelling

by wshobson · MIT license · ★ 39,857 on GitHub · updated Sep 21

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

---
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

Overview

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

Manual install (npx, ZIP)

Claude Codenpx skills add wshobson/agents --skill data-storytelling -g -a claude-code

Claude Code (manual)

mkdir -p ~/.claude/skills && curl -sL https://codeload.github.com/wshobson/agents/tar.gz/4236bb91f839 \
  | tar -xz -C ~/.claude/skills --strip-components=4 agents-4236bb91f839/plugins/business-analytics/skills/data-storytelling

Windows (PowerShell)

New-Item -ItemType Directory -Force "$HOME\.claude\skills" | Out-Null; Invoke-WebRequest "https://m.agentalley.io/zip/514280add15f56d4b2ad/data-storytelling.zip" -OutFile "$env:TEMP\data-storytelling.zip"; Expand-Archive "$env:TEMP\data-storytelling.zip" -DestinationPath "$HOME\.claude\skills" -Force

Claude.ai / desktopDownload the ZIP and upload it under Settings → Capabilities → Skills.

Codex, Cursor, other agentsPoint them at SKILL.md. The other files are plain text.

Connects with Agent Alley MCP · agentalley.io/mcp

Files included

SKILL.md2.1 KB
references/1 file · 10.1 KB

Read the files here

wshobson/4236bb92 files

SKILL.md2.1 KB

SKILL.md

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PreviewCode

Outline

RawView on GitHub

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

1	---
2	name: data-storytelling
3	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.
4	---
5
6	# Data Storytelling
7
8	Transform raw data into compelling narratives that drive decisions and inspire action.
9
10	## When to Use This Skill
11
12	- Presenting analytics to executives
13	- Creating quarterly business reviews
14	- Building investor presentations
15	- Writing data-driven reports
16	- Communicating insights to non-technical audiences
17	- Making recommendations based on data
18
19	## Core Concepts
20
21	### 1. Story Structure
22
23	```
24	Setup → Conflict → Resolution
25
26	Setup: Context and baseline
27	Conflict: The problem or opportunity
28	Resolution: Insights and recommendations
29	```
30
31	### 2. Narrative Arc
32
33	```
34	1. Hook: Grab attention with surprising insight
35	2. Context: Establish the baseline
36	3. Rising Action: Build through data points
37	4. Climax: The key insight
38	5. Resolution: Recommendations
39	6. Call to Action: Next steps
40	```
41
42	### 3. Three Pillars
43
44	\| Pillar \| Purpose \| Components \|
45	\| ------------- \| -------- \| -------------------------------- \|
46	\| Data \| Evidence \| Numbers, trends, comparisons \|
47	\| Narrative \| Meaning \| Context, causation, implications \|
48	\| Visuals \| Clarity \| Charts, diagrams, highlights \|
49
50	## Detailed patterns and worked examples
51
52	Detailed pattern documentation lives in `references/details.md`. Read that file when the navigation tier above is insufficient.
53
54	## Best Practices
55
56	### Do's
57
58	- Start with the "so what" - Lead with insight
59	- Use the rule of three - Three points, three comparisons
60	- Show, don't tell - Let data speak
61	- Make it personal - Connect to audience goals
62	- End with action - Clear next steps
63
64	### Don'ts
65
66	- Don't data dump - Curate ruthlessly
67	- Don't bury the insight - Front-load key findings
68	- Don't use jargon - Match audience vocabulary
69	- Don't show methodology first - Context, then method
70	- Don't forget the narrative - Numbers need meaning
71