skills/lyndonkl/claude/visual-storytelling-design

visual-storytelling-design

SKILL.md

Visual Storytelling Design

Table of Contents


Read This First

What This Skill Does

This skill helps you transform data into compelling visual narratives — data journalism, presentations, infographics, and interactive stories that communicate insights through narrative structure.

Core principle: People naturally seek stories with cause-effect and chronology. Structuring data as narrative aids comprehension and retention.

Why It Matters

Challenges of data storytelling:

  • Raw data is a heap of facts — hard to process
  • Visualizations can be misinterpreted without guidance
  • Readers skim, don't read thoroughly
  • Need emotional engagement AND factual accuracy

How cognitive principles help:

  • Narrative structure chunks information meaningfully (Context → Problem → Evidence → Insight)
  • Annotations guide attention to key insights (prevent misinterpretation)
  • Progressive disclosure reveals complexity gradually (scrollytelling)
  • Framing provides context for accurate interpretation

When to Use This Skill

Use this skill when:

  • ✓ Creating data-driven articles, reports, or presentations
  • ✓ Designing infographics or data visualizations with narrative
  • ✓ Building scrollytelling or interactive data experiences
  • ✓ Annotating charts to guide interpretation
  • ✓ Framing data with honest context and comparisons

Do NOT use for:

  • ✗ Learning cognitive principles (use cognitive-design)
  • ✗ Implementing D3.js visualizations (use d3-visualization)
  • ✗ Evaluating designs (use design-evaluation-audit)
  • ✗ Checking for misleading patterns (use cognitive-fallacies-guard)

Story Design Workflow

Time: 1-2 hours

Copy this checklist and track your progress:

Story Design Progress:
- [ ] Step 1: Define Narrative
- [ ] Step 2: Choose Structure
- [ ] Step 3: Apply Cognitive Techniques
- [ ] Step 4: Review for Clarity & Integrity

Step 1: Define Narrative

Determine the story arc: What's the context? What's the question/problem? What data answers it? What's the insight? Choose an opening strategy: lead with human impact, surprising finding, or visual.

Resource: Narrative Techniques — Narrative Structure section

Step 2: Choose Structure

Select a template and pattern that fits your story type, audience, and medium. Options include step-by-step article, magazine style, annotated chart, interactive exploration, or presentation deck.

Resource: Storytelling Patterns — Templates and Decision Matrix

Step 3: Apply Cognitive Techniques

Add annotations (callouts, arrows, shaded regions, direct labels). Apply framing with baselines, comparisons, and denominator clarity. Use scrollytelling for progressive revelation if web-based. Consider visual metaphors.

Resource: Narrative Techniques — Annotations, Scrollytelling, Framing sections

Step 4: Review for Clarity & Integrity

Verify the story is honest (no cherry-picking, balanced framing), clear (insight obvious in 5 seconds), and complete (sources cited, limitations noted). Use design-evaluation-audit for systematic evaluation and cognitive-fallacies-guard for integrity verification.


Path Selection Menu

Path 1: Build Narrative Structure

Choose this when: Starting a data story and need to define the narrative arc and opening strategy.

Go to Narrative Techniques — Sections 1-2


Path 2: Master Annotation

Choose this when: Adding annotations to guide interpretation of existing charts and visualizations.

Go to Narrative Techniques — Section 3


Path 3: Design Scrollytelling

Choose this when: Building web-based progressive revelation experiences.

Go to Narrative Techniques — Section 4


Path 4: Apply Framing & Metaphors

Choose this when: Providing context, baselines, comparisons, and visual metaphors.

Go to Narrative Techniques — Sections 5-6


Quick Reference

5 Storytelling Principles

  1. Lead with insight, not topic — Title: "Remote workers report 23% higher satisfaction" not "Remote work survey results"
  2. Annotate the insight — Don't make readers discover it; point it out with callouts
  3. Provide context — Baselines, historical comparisons, denominators for every percentage
  4. One change at a time — Scrollytelling: highlight OR annotate, not both simultaneously
  5. Be honest — Show full data, acknowledge limitations, avoid cherry-picking

Guardrails

This skill does NOT: Implement code, evaluate general usability, teach cognitive theory, or check for misleading patterns.

This skill DOES: Provide narrative structure, annotation techniques, scrollytelling patterns, framing guidance, story templates, and quality checklists for data storytelling.

Weekly Installs
7
Repository
lyndonkl/claude
GitHub Stars
36
First Seen
14 days ago
Installed on
gemini-cli7
github-copilot7
codex7
amp7
cline7
kimi-cli7