Product Analysis
SkillMediaNormalizes 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.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Product Analysis skill
What this skill tells your AI
The instructions your AI receives, as published by supercmohq/supercmo-skills in skills/analyzing-products/SKILL.md and read by ahel’s review.
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 withimage_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.
Signals
- GitHub stars
- 38
- Forks
- 5
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
analyzing-products- Source
- github.com/supercmohq/supercmo-skills