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data-storytelling

Transform data into compelling narratives using visualization, context, and persuasive structure

Install / Use

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

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

84/100

Supported Platforms

Universal

Our assessment of data-storytelling

data-storytelling scores 84/100 on our quality scale, 121st of 205 Data & Analytics skills we index.

Its SKILL.md is 2.1 KB long, well organised into 10 sections with 2 code examples: moderately detailed.

With 39,920 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
20/30
Structure
18/20
Description
12/15
Adoption
20/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 5 days ago, so data-storytelling is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.

Automated pattern scan on 2026-09-25. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

data-storytelling compared with similar skills

All 4 of these similar skills score higher than data-storytelling; compare them before choosing.

SkillScoreStarsUpdatedFormat
data-storytelling (this skill)by wshobson8439.9k5d agoSKILL.md
algorithmic-artby anthropics100177.9k3d agoSKILL.md
pptxby anthropics100177.9k3d agoSKILL.md
designby nextlevelbuilder100130.2k4d agoSKILL.md
ui-ux-pro-maxby nextlevelbuilder100130.2k4d agoSKILL.md

Frequently asked questions

How do I install data-storytelling?
Run npx skills add wshobson/agents --skill data-storytelling. The install tabs above show the steps for each supported agent.
Which AI agents does data-storytelling work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is data-storytelling safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is data-storytelling still maintained?
The repository was last updated 5 days ago, so data-storytelling is actively maintained.

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

Related Skills

View on GitHub
GitHub Stars39.9k
CategoryData
Updated5d ago
Forks4.3k

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions