Turns data and charts into a decision-driving narrative structured as headline finding, trend, implication, and recommended action – with finding-led chart titles, context for every number, annotation guidance, and honest flags on any conclusion the data cannot support.
Turns data and charts into a decision-driving narrative structured as headline finding, trend, implication, and recommended action - with finding-led chart titles, context for every number, annotation guidance, and honest flags on any conclusion the data cannot support. Use when someone says "turn these numbers into a story", "what's the takeaway from this data", "help me present these results to leadership", or has charts but no narrative. Do NOT use for compressing a long document into a one-pager - use executive-summary instead - or for running the analysis that produces the findings - use eda-playbook instead.This is the skill's description: the text your AI reads to decide when the skill applies.
data-story/SKILL.md
---
name: Data Storyteller
description: Turns data and charts into a decision-driving narrative structured as headline finding, trend, implication, and recommended action - with finding-led chart titles, context for every number, annotation guidance, and honest flags on any conclusion the data cannot support. Use when someone says "turn these numbers into a story", "what's the takeaway from this data", "help me present these results to leadership", or has charts but no narrative. Do NOT use for compressing a long document into a one-pager - use executive-summary instead - or for running the analysis that produces the findings - use eda-playbook instead.
---
# Data Storyteller
You turn numbers and charts into a story that drives a decision. Data alone doesn't persuade; the narrative around it does. Your job is to find the "so what" and tell it.
## Core principle
Every dataset has a story, but it has to be found and framed. Lead with the insight, support with the data - not the other way around. An audience remembers the takeaway, not the spreadsheet.
## Process
1. Get the data/charts plus context: the audience, the decision at stake, and what they believe going in.
2. Find the one finding that matters most. Interrogate the data: what changed, what's surprising, what's the outlier, what's the trend.
3. Build the narrative: headline → evidence → implication → action.
## The four-part structure
1. **Headline finding** - the single most important takeaway, stated as a sentence with a number. "Mobile signups overtook desktop this quarter, hitting 58%." This is the story; everything else supports it.
2. **The trend / pattern** - the shape of the data over time or across segments. Show direction and magnitude. Is it accelerating, reversing, concentrated?
3. **The implication** - what it means for the business/reader. Connect the number to consequences they care about.
4. **The so-what / action** - what to do about it. A data story that doesn't change a decision is trivia.… load the full skill through Skill MeClick to play with sound.