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.
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.
npx skills add ddcat-ai/open-ai-canvas --skill ecom-selling-point-infographicgit clone --depth 1 https://github.com/ddcat-ai/open-ai-canvasWrote 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.
[](https://agentmods.dev/skills/ddcat-ai/open-ai-canvas/ecom-selling-point-infographic)<a href="https://agentmods.dev/skills/ddcat-ai/open-ai-canvas/ecom-selling-point-infographic"><img src="https://agentmods.dev/badge/skills/ddcat-ai/open-ai-canvas/ecom-selling-point-infographic/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.
<a href="https://agentmods.dev/skills/ddcat-ai/open-ai-canvas/ecom-selling-point-infographic"><img src="https://agentmods.dev/badge/skills/ddcat-ai/open-ai-canvas/ecom-selling-point-infographic.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00052 | $0.00345 |
| Opus 5.5 | $0.00021 | $0.00138 |
| Sonnet 5.5 | $0.00010 | $0.00069 |
| Haiku 4.5 | $0.00005 | $0.00034 |
Grade A, and why
ecom-selling-point-infographic 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.
What it actually says
卖点信息图
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。纯图模式不调用本技能。
执行方法
把本页已确认卖点转为一个标题和2–4组短说明，选择侧栏、细引线、编号或对照组件，依据真实部位安排内容。
图片执行要求
商品占主要画面，标签对齐对应部位；标题、正文、数字建立字号层级，图标只表示已知功能，避免四角气泡机械重复。
交付核对
核对标签指向、文字原文、数字单位和手机可读性，不能用虚构数值当数字主视觉。
来源与适配
https://github.com/xianyu110/ecommerce-image-skills/blob/f4566fdc812584425728862ad8e08c90883d81ee/skills/selling-point-infographic/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。
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.
- yesterday First seen · 23 lines · 52 tokens per session scan A a51a27952385
ecom-selling-point-infographic is a skill published in the GitHub repository ddcat-ai/open-ai-canvas (1,677 stars, last pushed today), licensed MIT. It adds 52 tokens to every session and 345 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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