data-storytelling

Name: data-storytelling
Author: wshobson

13kinstalls4.1kforks

How to install data-storytelling?

wshobson/agents/data-storytelling

$npx -y skills add wshobson/agents --skill data-storytelling

Installs into the current project.

Summary

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

Files · 1

View on GitHub

SKILL.md

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

People who liked this also viewed

6 picks

Type

data-storytelling

13kinstalls4.1kforks

View on GitHub

How to install data-storytelling?

wshobson/agents/data-storytelling

$npx -y skills add wshobson/agents --skill data-storytelling

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

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

People who liked this also viewed

6 picks

Type