data-story-finderlisted
Install: claude install-skill ur-grue/autopunk-media-skills
# Data Story Finder
## What This Skill Does
Identifies the newsworthy story or stories hidden inside a dataset before any writing begins — surfacing angles, outliers, trends, and comparisons that are genuinely publishable.
## When To Use This Skill
- You have a dataset but are unsure which part of it is actually news
- You need to pitch a data story to an editor and want compelling angles, not just descriptions
- You want to stress-test a dataset before committing reporting time to a particular angle
- A PR or institution has released data and you want to find what they are not publicising
## What You Need To Provide
**Required:** A description of what the dataset contains — column headers, row count, time period covered, and source. Include a small representative sample (5–20 rows) if possible.
**Optional:** The institution or event the data came from; any story hypothesis you already have; publication type and audience.
## How the Assistant Approaches This
1. Reads the dataset description and sample to understand the structure, variables, and coverage period.
2. Applies five standard news-value lenses: magnitude, change over time, geographic variation, outliers, and hidden/buried comparisons.
3. Generates a ranked list of potential story angles with a plain-language summary of what makes each newsworthy, what data point supports it, and what additional reporting would be needed to publish it.
## Output Format
A structured document with: a one-paragraph overview of what