ecom-industry-tg

ecom-industry-tg is a skill for Claude Code, Codex from ddcat-ai/open-ai-canvas. It costs 27 tokens per session (309 once invoked), scanned A, original, MIT.

An industry-specific product presentation method that selects scenes, layouts, and information based on a product's category and subcategory.

In plain words
What is it for?
Use it to plan toy and game images showing the complete product, known ways to play, visible pieces, steps, and suitable activity scenes.
Why use it?
It reduces the risk of using an unsuitable setting or inventing game features, parts, or included items.

Skill for Claude CodeCodex

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

Good fit Use it to plan toy and game images showing the complete product, known ways to play, visible pieces, steps, and suitable activity scenes.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ddcat-ai/open-ai-canvas/ecom-industry-tg
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-industry-tg
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-industry-tg

README.md
[![agentmods](https://agentmods.dev/badge/skills/ddcat-ai/open-ai-canvas/ecom-industry-tg/github.svg)](https://agentmods.dev/skills/ddcat-ai/open-ai-canvas/ecom-industry-tg)
Your own site
<a href="https://agentmods.dev/skills/ddcat-ai/open-ai-canvas/ecom-industry-tg"><img src="https://agentmods.dev/badge/skills/ddcat-ai/open-ai-canvas/ecom-industry-tg/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-industry-tg

Your own site · 80×15
<a href="https://agentmods.dev/skills/ddcat-ai/open-ai-canvas/ecom-industry-tg"><img src="https://agentmods.dev/badge/skills/ddcat-ai/open-ai-canvas/ecom-industry-tg.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 27 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 309 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 $0.00027 $0.00309
Opus 5.5 $0.00011 $0.00124
Sonnet 5.5 $0.00005 $0.00062
Haiku 4.5 $0.00003 $0.00031

Measured 2d ago against content hash d7ef02069d1e, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ecom-industry-tg 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 2d ago.

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-industry-tg/SKILL.md · 19 lines

What it actually says

tg 行业方案

执行方法

先定位本轮具体子品类,优先采用最近上级的专属方法。行业场景候选:真实桌面、游戏或合适的活动环境;观察重点:可见部件、玩法关系和已确认包含项;叙事候选:完整玩具或游戏→已知玩法→实际互动→可见部件→不同合理玩法场景→已知配置→趣味收束

图片执行

围绕当前子品类和本商品证据选用场景、动作与真实部件;信息结构参考:玩法大图、步骤编号、真实部件与场景组合;字体参考:活力圆黑或游戏展示字,说明清晰。已选风格、无字与无人物设置优先,不把父类的功能或部件推断成本商品事实。

核对

核对分类、子品类、参考素材职责、真实部件、已知规格与行业使用关系;继承方法不代表当前叶级品类已经独立质检。

来源

魅夜原创创作方法;分类依据为 Shopify Product Taxonomy 2026-10,发布文件校验值见 ecommercecatalog/data/source.json。

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. 2d ago First seen · 19 lines · 27 tokens per session scan A d7ef02069d1e

Subscribe to this mod's changes

ecom-industry-tg is a skill published in the GitHub repository ddcat-ai/open-ai-canvas (1,677 stars, last pushed yesterday), licensed MIT. It adds 27 tokens to every session and 309 once invoked, about $0.0001 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.

Related

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ecom-industry-tg next to 6 skills from other repositories
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