data-storytelling — quality + safety report

In the Skillier index (wshobson-agents__data-storytelling) · scanned 2026-06-03 · engine: builtin+triage

A
Quality
98/100
Safety

✓ Clean — no heuristic safety flags surfaced.

Heuristic flags from the builtin scanner, which is known to over-flag (it trips on legitimate env-reading integrations, security skills, and library .eval calls). This is NOT an authoritative malicious verdict — re-scan with SkillSpector for the authoritative result. Run the authoritative scan →

Skillproof quality grade A

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Quality notes

No explicit output format / contract
low · quality · body
→ State the expected output format (structure, sections, or schema).

About this skill

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

📄 Read the SKILL.md
---
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
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Graded independently by Skillproof — nothing to sell the author. Quality is mechanical + corpus-grounded; safety flags are heuristic (builtin+triage), not a malicious verdict.