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data-storytelling

Transform raw data into narrative-driven presentations and reports with structured story frameworks.

2|1|Updated Aug 19, 2026
Search Tags:#narrative#data storytelling#executive summary#visualization#presentation#matplotlib#business review
One-click install
npx skills add https://github.com/lanceyuu/mimiwork --skill data-storytelling-lanceyuu
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-storytelling
Source: https://github.com/lanceyuu/mimiwork/tree/main/coworker/skills/builtin/data-storytelling
Command: npx skills add https://github.com/lanceyuu/mimiwork --skill data-storytelling-lanceyuu

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires matplotlib, pandas.

What problem does it solve? Raw analysis often fails to persuade because audiences cannot connect numbers to decisions. This Skill structures data findings into narratives with hooks, insights, and clear calls to action so stakeholders understand and act on the results. ## Core Features & Use Cases - Story Frameworks: Apply problem-solution, trend, and comparison narrative structures to organize findings. - Visualization Techniques: Use progressive reveal, before/after contrast, and annotated matplotlib charts to highlight key insights. - Presentation Templates: Build executive summary slides, data story flows, and one-page dashboard reviews. - Use Case: Turn a quarterly churn analysis into an executive deck that opens with the revenue impact, walks through the root cause, and ends with a budget request. ## Quick Start Use the data-storytelling skill to turn my Q4 sales analysis into an executive presentation with a clear recommendation.

Frequently Asked Questions about data-storytelling

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I present data analysis to executives?▼

Lead with the key insight and business impact rather than methodology. Use a story structure of hook, context, insight, recommendation, and call to action, supported by one clear visualization per point.

What is a good structure for a data-driven presentation?▼

A proven flow is headline, context, discovery, deep dive, recommendation, impact, and ask. Frameworks like problem-solution, trend, and comparison stories organize findings around a single decision the audience must make.

How do I write headlines for data reports?▼

Combine a specific number, the business impact, and actionable context, such as "Q4 Sales Beat Target by 23% - Here's Why". Avoid generic titles like "Sales Analysis" that carry no insight.

How do I visualize data for non-technical audiences?▼

Use progressive reveal to add one layer of information per slide, before/after comparisons to emphasize change, and annotated charts that mark key events and thresholds directly on the visual.

When should I not use a data storytelling approach?▼

Avoid it when the task is unrelated to communicating data insights, such as raw data cleaning or pipeline engineering. It also does not replace environment-specific validation, statistical review, or domain expert judgment.

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