Slime Amazon Design Skill

Six Codex skills that take an Amazon seller from product photos and competitor research to finished main images and A+ content.

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Skill

Extended access

Why this level

  • Scripts read the product photo and document folder and write files into the run folder
  • Image generation uses paid resources of your account
All reasons and checks

knight9629/slime-amazon-design-skill

Install

In your terminal, with SkillFoxx CLI

npx skillfoxx add skills/slime-amazon-design-skill

Detects the agents on your machine, shows the access level and pins the version.

Other ways to install

Access and checks

How we review

Extended accessThe tool runs code or makes network calls and only reads external data.

  • Scripts read the product photo and document folder and write files into the run folder
  • Image generation uses paid resources of your account

This is third-party code. Review the repository files before installing.

What it does

The set walks an Amazon listing through design step by step. The main skill `amazon-ai-design-workflow-orchestrator` reads the project folder, asks only for missing data and calls the rest: white reference images from real photos, a breakdown of competitor main images and A+ content, a brief of specifications and selling points, three style options with one sample each, then production with quality control. The output is files at exact sizes. If the source ratio is within one percent of the target, a script scales it and logs the correction in the manifest; otherwise the task goes back to generation. The repository description and instructions are in Chinese; the skills respond to requests in English as well. The models and generation quota are not part of the package.

Who it is for. Amazon sellers and listing designers who build main images and A+ content from real product photos.

Good fit when

  • A product has real photos and specifications and you need a full main image and A+ set for the US marketplace
  • Before choosing a look you want to study how competitors order and prove claims in their images
  • You want to pick a style from A, B and C samples before expensive generation starts
  • Finished images must be brought to exact sizes and checked before upload

Not a fit when

  • You need a single test image: the full flow is heavy for that, so ask for the quick mode explicitly
  • There are no real photos or specifications: the skill builds on authentic materials
  • You need the listing published on Amazon: the skill prepares images and publishes nothing

Example request

Use `$amazon-ai-design-workflow-orchestrator`: from this folder of photos and specs build a main image and A+ content for the US marketplace, and check the materials first.

Limitations

The package targets Codex and needs Python 3.10 or newer and Pillow. Real generation needs image tooling and quota on your own account, which the file install does not include. The author notes that installation and checks do not prove a full run on every platform. iPhone HEIC files must be converted to JPG first. The repository has no declared open-source license and is published for viewing and download. The install and usage guide is in Chinese.

How to disable. Delete the six skill folders from `$CODEX_HOME/skills` (by default `~/.codex/skills`). If you installed with `--backup`, earlier versions sit in a separate backup folder outside the skills directory.

FAQ

Which skills are in the set?

Six: the main `amazon-ai-design-workflow-orchestrator`, production `amazon-image-production-runner`, references `product-reference-composer`, competitor research `amazon-competitor-creative-research`, a selling point brief `amazon-product-selling-point-brief` and style samples `amazon-creative-style-sampler`.

How do I install it?

Download the archive from the release, open the folder in Codex and ask it to install the package. By hand: `python3 verify_package.py`, then `python3 install.py --check` and `python3 install.py`. With an older version use `python3 install.py --backup`.

What do I do after installing?

Open a new Codex task so the skill list reloads and call the main skill with a request about your materials folder. It checks the environment and photos first and then confirms the scope of work.

What happens with image sizes?

The 4:5 main image and desktop A+ have fixed sizes. If the source differs in ratio by no more than one percent it is scaled without cropping; otherwise it goes back to generation.

Which styles does the skill give?

Three options A, B and C with one sample each. After you choose, production continues in the same task and A+ parameters are confirmed on the way: type, language, desktop or phone.

Discussion

No questions or reviews yet.

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Comparison with similar tools

Cards that share the main search query, and how they differ.

ToolOfficialRepository starsMain difference
Slime Amazon Design Skill (this card)no84
clawEC cross-border trading agentsno75clawEC agents and skills for product selection across Amazon, TikTok, Shopee and Ozon
HasData Agent Skills: scraping and SERP APIyes14skills that call Google SERP and Amazon APIs and do no image design

README in short

The Chinese page describes version 1.0.2 and lists fixes: export, tracking of generated files, real photo detection, installation on Mac and the Basic A+ size. Then a table of six skills, requirements, installation through Codex or by hand and sample requests. It ends with integrity checks and a note that no license is declared.

README badge

Original SKILL.md

---
name: amazon-ai-design-workflow-orchestrator
description: "Use when the user invokes 史莱姆亚马逊设计skill or the Amazon 主图A+ / 主图+A+ design skill, asks for Amazon main-image and A+ workflow execution, or needs project-stage control across product references, research, style sampling, prompts, image2 generation, QC, and export."
---

# 史莱姆亚马逊设计skill

Skill version: `1.0.0`


This is the stable `1.0.0` release and the default for ordinary Amazon main-image/A+ requests.

## Image model default

`LATEST_IMAGE_MODEL`: apply the `imagegen` model policy before generation. Resolve the newest stable model from current official image-generation documentation at the start of a run; as checked on `2026-10-15`, prefer `gpt-image-2.5-sunburst` for product fidelity and precise edits. Keep that selection for the run and recheck for a new run. `image2`, `provider: image2` and `IMAGE2_PROVENANCE_GATE` are compatibility identifiers, not a model-version pin; they allow a newer model on the same supported route.

Select the model through a supported execution parameter or verify a current first-party runtime guarantee. Prompt text cannot select a backend. If the required latest model cannot be selected or verified, report `blocked: model_selection_unavailable` before generation; record actual model `unknown` and verification `unverified`, and do not claim an upgrade. A latest-model preference does not authorize a new paid API route or spending. Preserve current product, reference, copy, scope and QC gates and all historical generation records.

The controller records target model, actual model when exposed, verification status and official source in the existing run notes, separately from provider. Before dispatch, inline the resolved model/route and verification state as execution instructions outside the five-field image packet and outside the image prompt. Fresh workers must receive these instructions without reading extra files; if they cannot execute the verified route, they return a standard `OTHER` failure with `model_selection_unavailable`. Do not dispatch an unverified route to satisfy a strict latest-model requirement.

## Goal

Act as the full-flow controller for Amazon main-image and A+ production.

Calling this skill for a new image set means `FULL_FLOW` by default. Directed edits to an approved existing baseline follow `SCOPED_REVISION` below. Use `QUICK_TASK` only when the user explicitly asks for a sample, test image, first-screen test, or an ordinary 1-3 image task. A quick task stays in the current task and does not count as full-flow progress.

`FULL_FLOW_EXCLUSIVE_CONTROL`: once a request enters `FULL_FLOW`, generic brainstorming, visual-companion pages, HTML/CSS mockups, and nearby helper workflows may not replace, pause, or relabel the state machine unless the user explicitly requests that separate artifact. “先出样” under time pressure does not silently convert an already-invoked full run into `QUICK_TASK`.

The controller must:

- inspect the project before asking questions;
- ask only for missing production-scope fields;
- protect product truth and local details before style;
- generate at least three white-background reference images from the photographed product images at the beginning of the workflow;
- resolve a dynamic Product Facts Gate before big-brand research, style samples, or full production, asking only about remaining blocking facts;
- use the lightest valid reference route;
- research competitors and current big-brand cases for every product;
- find references by visual/layout purpose, reuse explicitly liked favorites, and refresh rejected candidates with minimal user input;
- compare three styles with one representative image per style;
- carry product-exposure role checks into the compact production context and formal production planning;
- continue selected-style formal production in the same task by default;
- generate every approved raw slot before centralized finished-image QC;
- use bounded subagent parallelism for independent research, style, planning, prompt, generation, and QC work when subagents are available;
- keep the controller as the only writer of canonical facts, decisions, state, and final manifests;
- create worker documents only when a worker/subagent is actually dispatched;

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