product-meaning-extractor

Solid

Deep product analysis before creating videos, presentations, or ads. Use when: 'analyze product', 'extract value', 'product brief', 'what makes this product special', 'prepare brief', 'understand the product', 'video brief'. Takes a URL or product description and outputs a structured brief with core insight, enemy, transformation, proof, mechanism, and emotional hooks. Based on JTBD, StoryBrand, Obviously Awesome (April Dunford), and Value Proposition Canvas frameworks. Do NOT use for writing the script or scene timing (use video-narrative-arc), scoring an existing script (use script-evaluator), or rendering video (use remotion-production-guide); this is the upstream brief-only step before any script is written.

AI & Automation 138 stars 20 forks Updated today MIT

Install

View on GitHub

Quality Score: 86/100

Stars 20%
71
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
80
License 10%
100
Description 5%
100

Skill Content

# Product Meaning Extractor Extract the REAL value from a product before writing a single line of video/presentation code. Without this step, content is a flat list of features. With it, content tells a story. ## Why This Exists Most product videos fail because they skip analysis. They grab text from a landing page and lay it over animations. The result: "We have feature A, B, C. Try us." - nobody watches past 3 seconds. This skill forces you to find what actually matters: the enemy, the transformation, the mechanism, and the emotional hook. Everything else flows from these. ## Process ### Step 1: Gather Raw Material **From the product URL:** 1. Visit the site, extract ALL text (hero, features, pricing, about, FAQ) 2. Screenshot key visuals (hero, before/after, product shots) 3. Extract brand colors from CSS (`--primary`, `--accent`, meta `theme-color`) 4. Note the tone: formal/casual, technical/simple, premium/accessible **From reviews/testimonials (if available):** 1. Find testimonials on the site itself 2. Check App Store / Product Hunt / G2 / Trustpilot / Reddit mentions 3. Extract VERBATIM customer phrases - their words always beat your words ### Step 2: The "So What?" Test For EVERY feature on the site, ask "So what?" until you reach the real value. Most features need 3-4 "so what?" iterations: ``` Feature: "Outputs .PSD with layers" So what? → "You can edit individual elements" So what? → "You don't redo the whole job if one thing is wrong" So what? → "It sa...

Details

Author
AnastasiyaW
Repository
AnastasiyaW/claude-code-config
Created
4 months ago
Last Updated
today
Language
Python
License
MIT

Bundled in these plugins

Similar Skills

Semantically similar based on skill content — not just same category