Normalizes a product into generation-ready facts — from an e-commerce URL (a clean description plus curated product images) or from a photo alone (category, how it's used, its moving/opening parts, and key visual details). Use when a product URL or photo needs turning into inputs for image/video generation, or when another skill needs product facts before generating.
Scanned 8/31/2026
Install to Claude Code
npx -y skills add SupercmoHQ/superCMO-skills --skill analyzing-products --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: analyzing-products
description: Normalizes a product into generation-ready facts — from an e-commerce URL (a clean description plus curated product images) or from a photo alone (category, how it's used, its moving/opening parts, and key visual details). Use when a product URL or photo needs turning into inputs for image/video generation, or when another skill needs product facts before generating.
license: Apache-2.0
metadata:
version: "0.1.0"
category: creative
summary: "Analyzes an e-commerce link or photo to map out your product's exact physical mechanics and extract clean reference images, building a highly accurate creative brief without any manual research or extraction."
---
# Product Analysis
Turn a product — an e-commerce **URL** or a bare **photo** — into clean, reusable facts for downstream
image/video generation: a tight description, curated product images, and how the product is physically
used. It's a building block: other skills call it at the input stage, before any generation.
## Workflow
### Step 1: Pick the mode and run it
| Input | Reference | What you produce |
| ----- | --------- | ---------------- |
| An e-commerce URL (Amazon, Shopify, AliExpress, any product page) | `references/url-extract.md` | A two-paragraph description + up to 5 downloaded, filtered product images |
| A product photo only (no URL, no description) | `references/photo-analysis.md` | Category + how it's used + moving/opening parts + key visual details |
Read **only** the matching reference and follow it end to end. If both a URL and a photo are given, run
the URL mode (richer) and keep the photo as one more reference image; if neither is given, there's
nothing to analyze — ask for one. Don't pause for confirmation — a URL (or photo) plus generation
intent means extract and proceed.
### Step 2: Hand off
Return the result to whoever called you, ready to drop into generation:
- **URL mode** → the description and the kept image files (local paths, usable as reference images).
- **Photo mode** → the category, how it's used, any moving or opening parts, and the key visual details.
Don't rank the product's market position — the calling skill decides that from packaging cues. Your
job is the objective facts.
## Edge cases
- **The URL can't be extracted** (no result, or the extractor isn't set up) → ask for a product photo
instead and switch to photo mode.
- **Every image fails the filter** (faces, wrong variant, not a product shot) → keep the single
cleanest, or hand off the description alone and say plainly that no clean image survived.
- **A supplied photo is too unclear to read** (blurry, cropped, ambiguous) → say what you can't
determine and ask for a clearer shot rather than guessing the mechanic.
- **Neither a URL nor a photo** → ask for one; there is nothing to analyze.
## Reference
- `references/url-extract.md` — the URL pipeline: `url_extraction` → download the images → filter them
with `image_analysis` → write the description.
- `references/photo-analysis.md` — the photo pipeline: category, how it's used, moving/opening parts,
and the visual details to preserve.
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