ai-amazon-storefront-design

ai-amazon-storefront-design Amazon Store Optimization Assistant

Overview

The Amazon Store Optimization Assistant is used to answer "Can the store homepage convert?", organize materials, clean data, and identify action items. It is suitable for operations, product, and sales software to invoke after clarifying business goals, content materials, or analysis targets. It combines inputs such as product, store, or operational materials, pasted product information, store pages, review materials, competitor information, sales goals, or channel requirements, organizes key context, and outputs product/store diagnostics, selling points and risk alerts, and operational action recommendations for further execution, review, or delivery. Capability positioning supplement: skills.sh hot signals show that amazon-storefront-design has user demand; the platform presents it as an ecommerce_retail business assistant directory, outputting reviewable diagnostics, recommendations, or production preparation packages.

When to Use

Applicable Scenarios

Users ask questions like "Can the store homepage convert?" and need to quickly break down goals, determine priorities, and form executable results
Operations, product, and sales software need to generate product/store diagnostics, selling points and risk alerts, and operational action recommendations around the Amazon Store Optimization Assistant
Users have already prepared operational goals (explaining the click, conversion, repurchase, inventory, profit, review, or campaign goals they hope to optimize), target buyers (explaining target buyers, market, platform, channel, or usage scenario), and product or store links (filling in publicly accessible product, store, competitor, review, or platform page links) and hope to organize them into executable analysis or optimization results
Users need to turn materials related to the Amazon Store Optimization Assistant into clear conclusions, priorities, and next actions

How to Invoke

Directly call the AI Skills API through the exported Python runner:

Command Examples

Basic Invocation

python3 scripts/run.py --params '{}'

Invocation with Common Parameters

python3 scripts/run.py --params '{"goal":"运营目标"}'

Parameter Description

Parameter	Type	Required	Default	Description
`goal`	string	No	-	Explain the click, conversion, repurchase, inventory, profit, review, or campaign goals you hope to optimize
`audience`	string	No	-	Explain the target buyers, market, platform, channel, or usage scenario
`materialUrl`	string	No	-	Fill in publicly accessible product, store, competitor, review, or platform page links; a complete accessible URL is required
`materialFile`	string	No	-	Upload product materials, review tables, competitor screenshots, operational data, store plans, or asset files
`materialText`	string	No	-	Paste product information, store pages, review materials, competitor information, sales goals, or channel requirements
`brandRequirements`	string	No	-	Supplement platform rules, price boundaries, inventory constraints, brand restrictions, content that cannot be promised, or manual review priorities

See the complete machine-readable parameter structure at references/form-schema.json。

Parameter Value Reference

This skill currently has no categorical parameters that require additional table lookup.

Supported Input Formats

The current skill directly accepts JSON parameters; if the parameters contain a link field, please pass a complete, accessible URL.

Example request

The example parameters below can be passed directly to scripts/run.py, and the runner will send them to the AI Skills API.

python3 scripts/run.py --params '{"goal":"运营目标"}'

Equivalent --params JSON：

{
  "goal": "运营目标"
}

Example return result

{
  "success": true,
  "data": {
    "message": "示例结果请以技能真实返回结构为准。"
  },
  "meta": {
    "executionTime": 842,
    "cached": false
  }
}

Deliverables

Product/store diagnosis, selling points and risk alerts, operational action recommendations: organize core results around the user's goals that can be directly read, reviewed, or delivered.
Interpretation of input materials: combine the operational goal (explain the click, conversion, repurchase, inventory, profit, review, or campaign goals you want to optimize.), target buyers (explain the target buyers, market, platform, channel, or use case.), product or store links (fill in publicly accessible product, store, competitor, review, or platform page links.) to extract key context and basis for judgment.
Next steps: provide priorities, execution suggestions, or a content framework that can be further processed.

Suggestions for using the results

First determine whether the output answers the user's core question about the "Amazon store optimization assistant".
Then check whether the results cover product/store diagnosis, selling points and risk alerts, operational action recommendations, and whether they provide clear next steps.
If there is little input material, it is recommended to have the user supplement the goals, audience, constraints, or source materials before running.

Preparation before running

AISKILLS_BASE_URL: default https://ai-skills.ai
AISKILLS_API_KEY: required, used for authenticated calls
AISKILLS_TENANT_ID: default default