How do I install the Analyzing Products skill?

Run npx skillmds@latest add aiskillstore/analyzing-products in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Analyzing Products safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Analyzing Products?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Analyzing Products free to use?

Yes. Installing skills from SkillMD is free. This skill is licensed under Apache-2.

Who published Analyzing Products?

aiskillstore (@aiskillstore) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Analyzing Products by aiskillstore — Agent Skill

Name: Analyzing Products
Rating: 4.2 (5 reviews)
Author: aiskillstore

Analyzing Products

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.

aiskillstore Updated Sep 9, 2026

File contents

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.

---name: analyzing-productsdescription: 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--- # 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.

Frequently asked questions