ai-marketing-skills/content-ops/scoring-rubrics/visual-quality.md
Alfred Claw a96d0d8889 Initial commit: 6 AI marketing skill categories
- growth-engine: Autonomous experiment engine (Karpathy autoresearch for marketing)
- sales-pipeline: RB2B router, deal resurrector, trigger prospector, ICP learner
- content-ops: Expert panel, quality gate, editorial brain, quote miner
- outbound-engine: Cold outbound optimizer, lead pipeline, competitive monitor
- seo-ops: Content attack briefs, GSC optimizer, trend scout
- finance-ops: CFO briefing, cost estimate, scenario modeler

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2026-03-27 20:14:52 -07:00

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Visual Quality Rubric (0-100)

For charts, data visualizations, infographics, diagrams, slide decks.

Data Accuracy & Integrity (0-25)

  • Numbers match the source data
  • Axes labeled correctly, scales not misleading
  • No cherry-picked timeframes or truncated axes
  • Source cited

Visual Clarity (0-25)

  • Can a viewer understand the main point in under 5 seconds?
  • Labels readable at expected display size
  • Color choices accessible (colorblind-safe)
  • No chart junk (unnecessary gridlines, 3D effects, decorative elements)

Insight Delivery (0-25)

  • Does the visualization tell a story or just display data?
  • Is the "so what?" obvious without explanation?
  • Annotations highlight the key takeaway
  • Title states the insight, not just the topic ("Revenue doubled in Q3" > "Revenue by quarter")

Design & Polish (0-25)

  • Consistent typography and color palette
  • Proper alignment and spacing
  • Brand-appropriate styling
  • Mobile/thumbnail readable if applicable