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 T8mars/T8-penguin-canvas --skill product-prompt-briefgit clone --depth 1 https://github.com/T8mars/T8-penguin-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/t8mars/t8-penguin-canvas/product-prompt-brief)<a href="https://agentmods.dev/skills/t8mars/t8-penguin-canvas/product-prompt-brief"><img src="https://agentmods.dev/badge/skills/t8mars/t8-penguin-canvas/product-prompt-brief/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/t8mars/t8-penguin-canvas/product-prompt-brief"><img src="https://agentmods.dev/badge/skills/t8mars/t8-penguin-canvas/product-prompt-brief.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 | $0.00039 | $0.00508 |
| Opus 5.5 | $0.00016 | $0.00203 |
| Sonnet 5.5 | $0.00008 | $0.00102 |
| Haiku 4.5 | $0.00004 | $0.00051 |
Grade A, and why
product-prompt-brief 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 1mo 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.
What it actually says
商品提示词整理 / Product prompt brief
把用户零散的商品信息、参考图说明和创作要求整理成可直接使用的完整提示词。纯文字资料也可以完成，不强迫用户上传图。用用户的语言写作，保持品牌语气；不擅自扩展成营销方案、多镜头广告或实际媒体生成。
优先保留用户明确的信息：主体是什么、谁会看、在哪里使用、必须保留什么、允许改变什么。区分已知事实与创意设定，不补写价格、功效、认证、模糊图片上的品牌字或不存在的卖点。仅当关键信息缺失到无法写出有意义提示词时，问一个最重要的问题；其余使用说明清楚的合理默认。
完整作品包含两部分：
- 可复制的提示词正文：自然连贯地说明主体身份与保留项、主体和环境的关系、构图/留白、光线/材质、用户明确指定的文字及比例。信息必须自足，不写“同上”“见之前那条”。
- 简短核对项：最多三个对这份要求真正重要的检查点；标明任何尚待用户确认的事实。不要把内部 ID、模型配置、检查记录塞进提示词正文。
用户提供了原稿时，先保留有效部分，再解决冲突、歧义或多余形容词。用户要求“只改背景”“缩短但保留中文文案”等限定修改时，其他事实和指定文字原样保留。若缩短会破坏必要信息，指出取舍而不是悄悄删掉。
长正文放入完整文本作品，聊天只说明改进点并提供后续修改方向。交付提示词不等于完成图片；此技能不发起图片、视频、上传或额外评审调用。用户改为想要成图时，说明可以切换到图片创作方法，保留现有提示词供用户使用，不擅自替换任务。
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.
- 1mo ago First seen · 23 lines · 39 tokens per session scan A f3ce87fc8d1b
product-prompt-brief is a skill published in the GitHub repository T8mars/T8-penguin-canvas (633 stars, last pushed yesterday), licensed MIT. It adds 39 tokens to every session and 508 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 2026-09-13.
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