Data Storytelling

Data Storytelling, published by wshobson under the MIT licence, teaches the agent to turn analysis into a narrative that drives a decision. The core structure is Setup, Conflict, Resolution, extended into a six-beat arc: hook, context, rising action, climax, resolution and call to action. Every story rests on three pillars: data as evidence, narrative for meaning and visuals for clarity. Its reference file supplies three story frameworks (problem-solution, trend and comparison), visual techniques such as progressive reveal, contrast and annotation, and templates for an executive summary slide and a one-page dashboard story.

It is for analysts presenting to executives, writing data reports or building a quarterly review. The rules are direct: lead with the so-what, use the rule of three, end with a clear next step, and avoid data dumps, buried insights, jargon and leading with methodology. It also includes guidance on headlines, transitions and how to state uncertainty. It does not produce charts or query data itself; it shapes how findings are presented.

In BusinessMCP the AI business analyst can use this playbook when summarising your workspace's analytics, pipeline or revenue for a stakeholder, so a weekly update opens with the finding and the recommended action rather than a list of metrics.