Agent skill · data analytics · aiskillstore
data-storytelling
Transform raw data into compelling narratives that drive decisions and inspire action.
Why this skill is useful
Provides structured frameworks and methodologies for transforming data into actionable narratives that the AI wouldn't generate on its own.
What it needs
About 7k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
Data Storytelling Transform raw data into compelling narratives that drive decisions and inspire action. Do not use this skill when The task is unrelated to data storytelling You need a different domain or tool outside this scope Instructions Clarify goals, constraints, and required inputs. Apply relevant best practices and validate outcomes. Provide actionable steps and verification. If detailed examples are required, open resources/implementation-playbook.md. Use this skill when Presenting analytics to executives Creating quarterly business reviews Building investor presentations Writing data-driven reports Communicating insights to non-technical audiences Making recommendations based on data Core Concepts 1. Story Structure 2. Narrative Arc 3. Three Pillars Pillar Purpose Components ------------- -------- -------------------------------- Data Evidence Numbers, trends, comparisons Narrative Meaning Context, causation, implications Visuals Clarity Charts, diagrams, highlights Story Frameworks Framework 1: The Problem-Solution Story Framework 2: The Trend Story Framework 3: The Comparison Story Visualization Techniques Technique 1: Progressive Reveal Technique 2: Contrast and Compare Technique 3: Annotation and Highlight Presentation Templates Template 1: Executive Summary Slide Template 2: Data Story Flow Template 3: One-Page Dashboard Story Writing Techniques Headlines That Work Transition Phrases Handling Uncertainty Best Practices Do's Start with the "so what" - Lead with insight Use the rule of three - Three points, three comparisons Show, don't tell - Let data speak Make it personal - Connect to audience goals End with action - Clear next steps Don'ts Don't data dump - Curate ruthlessly Don't bury the insight - Front-load key findings Don't use jargon - Match audience vocabulary Don't show methodology first - Context, then method Don't forget the narrative - Numbers need meaning Resources Storytelling with Data (Cole Nussbaumer) The Pyramid Principle (Barbara …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/data-storytelling