ecom-amazon-white-background

ecom-amazon-white-background is a skill for Claude Code, Codex from ddcat-ai/open-ai-canvas. It costs 46 tokens per session (333 once invoked), scanned A, original, MIT.

A product-image guideline for making a main listing image with a plain white background while keeping the real product, its shape, colour, logo, and included accessories. It removes the background and non-sale items without adding promotional text or props.

In plain words
What is it for?
It is for preparing white-background marketplace images, including edge, colour, logo, accessory, lighting, and contact-shadow checks.
Why use it?
It helps create a clean product image without losing parts of the item or changing its appearance.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It is for preparing white-background marketplace images, including edge, colour, logo, accessory, lighting, and contact-shadow checks.

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Install with agentmods
npx agentmods add skills/ddcat-ai/open-ai-canvas/ecom-amazon-white-background
About the project

影策 is an open-source workspace for AI film and short-video production, using a freeform canvas and structured workflows to organize scripts, characters, scenes, storyboards, media assets, and generated text, images, video, and audio. It is for creators who manage audiovisual projects through local or trusted deployments, with features for task tracking, asset management, timelines, and AI-agent workflows.

ddcat-ai/open-ai-canvas · 1,677 stars · on GitHub · yingce.tv

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add ddcat-ai/open-ai-canvas --skill ecom-amazon-white-background
Clone the repo
git clone --depth 1 https://github.com/ddcat-ai/open-ai-canvas

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for ecom-amazon-white-background

README.md
[![agentmods](https://agentmods.dev/badge/skills/ddcat-ai/open-ai-canvas/ecom-amazon-white-background/github.svg)](https://agentmods.dev/skills/ddcat-ai/open-ai-canvas/ecom-amazon-white-background)
Your own site
<a href="https://agentmods.dev/skills/ddcat-ai/open-ai-canvas/ecom-amazon-white-background"><img src="https://agentmods.dev/badge/skills/ddcat-ai/open-ai-canvas/ecom-amazon-white-background/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for ecom-amazon-white-background

Your own site · 80×15
<a href="https://agentmods.dev/skills/ddcat-ai/open-ai-canvas/ecom-amazon-white-background"><img src="https://agentmods.dev/badge/skills/ddcat-ai/open-ai-canvas/ecom-amazon-white-background.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 333 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00046 $0.00333
Opus 5.5 $0.00018 $0.00133
Sonnet 5.5 $0.00009 $0.00067
Haiku 4.5 $0.00005 $0.00033

Measured yesterday against content hash c55cde7bfdac, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ecom-amazon-white-background scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

backend/internal/ecommerceskills/packages/ecom-amazon-white-background/SKILL.md · 23 lines

What it actually says

纯白主图保真

输入与适用范围

使用本轮商品事实、参考素材职责、用户提示词、目标平台及已确认风格。

执行方法

从商品图锁定轮廓、颜色、Logo和包含的配件,只移除背景与非销售物,保留完整真实商品。

图片执行要求

纯白无缝背景、柔和均匀布光与轻微接触阴影;不加广告文字、徽章、道具、水印;商品原有印字保留,服从本轮比例与平台设置。

交付核对

检查背景、完整边缘、颜色及印字,不能因无新增文字而抹去原有Logo。

来源与适配

https://github.com/xianyu110/ecommerce-image-skills/blob/f4566fdc812584425728862ad8e08c90883d81ee/skills/amazon-white-background/SKILL.md 版本:f4566fdc812584425728862ad8e08c90883d81ee。按 MIT 许可改编;仅保留适合本工作台的创意方法,不导入来源脚本、指定供应商、固定页数或平台示例阈值。

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 23 lines · 46 tokens per session scan A c55cde7bfdac

Subscribe to this mod's changes

ecom-amazon-white-background is a skill published in the GitHub repository ddcat-ai/open-ai-canvas (1,677 stars, last pushed today), licensed MIT. It adds 46 tokens to every session and 333 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-11-05.

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