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Meta Description Grader

Use cases

Auditing meta descriptions at scale Comparing your descriptions vs competitors Finding weak descriptions to improve Training teams on meta description best practices

Four-dimension GPT-4 grading: emotional hook/power verbs (0-10), clear benefit statement (0-10), active voice usage (0-10), urgency/interest creation (0-10).

Total score out of 40.

Model selection: gpt-4o-mini (default), gpt-4o, gpt-4.1.

Single and bulk modes with column mapping.

Streamlit App Requires API Key

Platform

Browser-based (no installation required)

Input

OpenAI API key

Meta description text (single) or file (bulk)

Optional: URL for context

Output

Per-criterion scores (0-10): hook, benefit, voice, urgency. Total /40 with summary stats (average, max, min) for bulk.

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Features

  • Four 0-10 scoring dimensions (total /40)
  • Emotional hook and power verb detection
  • Benefit statement analysis
  • Active voice and urgency scoring
  • Bulk CSV/Excel with summary statistics

How to use

  1. 1 Enter your OpenAI API key
  2. 2 Select GPT model (gpt-4o-mini recommended)
  3. 3 Paste description or upload CSV/Excel
  4. 4 Map columns for bulk analysis
  5. 5 Review color-coded criterion scores
  6. 6 Download with total scores and averages

Want me to run this for you?

I offer this as a managed service. You get the insights without touching the tool.

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