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weight-dimensions

Calculate audience dimension relevance weights for marketing angle prioritization.

1|Updated Apr 20, 2026
Search Tags:#copywriting#strategy#scoring#audience#angles#weighting
One-click install
npx skills add https://github.com/Largo2z9/phantomos --skill weight-dimensions
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: weight-dimensions
Source: https://github.com/Largo2z9/phantomos/tree/main/.skills/skills/weight-dimensions
Command: npx skills add https://github.com/Largo2z9/phantomos --skill weight-dimensions

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill solves the problem of unclear audience prioritization by calculating which audience dimensions matter most for each marketing angle, helping strategy systems focus on the strongest relevance signals.

Core Features & Use Cases

  • Contextual Dimension Weighting: Evaluates eight canonical audience dimensions and assigns relevance weights for each compatible angle.
  • Strategy Alignment: Uses audience profiles, angle lineage, and copywriting doctrine references to inform scoring inputs for downstream decision systems.
  • Validation and Persistence: Produces validated dimension weight outputs with sum checks, dominant dimension identification, and controlled context updates.

Quick Start

Ask the AI to compute dimension weights for a configured audience and its available marketing angles using the weight-dimensions skill.

Frequently Asked Questions about weight-dimensions

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I calculate audience dimension weights for marketing angles?▼

Audience dimension weighting evaluates eight canonical audience dimensions against your marketing angles, assigning relevance weights to identify the strongest signals for copywriting and DTC strategy workflows.

What is the best way to prioritize marketing angles using audience profiles?▼

Prioritize marketing angles by computing dimension relevance weights from structured audience profiles and angle lineage, producing validated normalized scores that highlight your dominant audience traits.

How do I improve scoring accuracy for DTC copywriting frameworks?▼

Improve DTC copywriting scoring accuracy by applying contextual dimension weighting to audience profiles, using angle lineage and doctrine references to generate validated, normalized weight outputs for decision matrices.

Do I need structured audience profiles to compute dimension relevance scores?▼

Yes, computing dimension relevance scores requires structured audience profiles and compatible angle data to validate normalized weights and accurately identify dominant dimensions for your strategy workflows.

How does dominant dimension identification work in marketing strategy scoring?▼

Dominant dimension identification evaluates eight canonical audience dimensions against compatible angles, calculating relevance weights and performing sum checks to validate the highest prioritization weight for your strategy.

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