← ClaudeAtlas

data-story-finderlisted

Identifies the newsworthy story or stories hidden inside a dataset before any writing begins — surfacing angles, outliers, trends, and comparisons that are genuinely publishable.
ur-grue/autopunk-media-skills · ★ 8 · Data & Documents · score 81
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