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 bozhouDev/video-skills-toolkit --skill douyin-covergit clone --depth 1 https://github.com/bozhouDev/video-skills-toolkitWrote 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/bozhoudev/video-skills-toolkit/douyin-cover)<a href="https://agentmods.dev/skills/bozhoudev/video-skills-toolkit/douyin-cover"><img src="https://agentmods.dev/badge/skills/bozhoudev/video-skills-toolkit/douyin-cover/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/bozhoudev/video-skills-toolkit/douyin-cover"><img src="https://agentmods.dev/badge/skills/bozhoudev/video-skills-toolkit/douyin-cover.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00374 | $0.04203 |
| Opus 5 | $0.00187 | $0.02101 |
| Sonnet 5 | $0.00075 | $0.00841 |
| Haiku 4.5 | $0.00037 | $0.00420 |
Grade A, and why
douyin-cover 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Douyin Cover
为当前项目生成短视频封面图。默认目标是:标题一眼能读懂,画面简约大方且有点击理由,泊舟 IP 人物稳定可识别。技能只提供比例、版式、文字准确性和质量检查框架,不预设具体场景、道具或画面元素。
先读这些
- 每次使用先读
references/ip-persona.md,确认泊舟 IP 的稳定特征。 - 每次正式设计前读
references/design-playbook.md,从标题类型选择合适的视觉策略。 - 需要具体锚点位置、配色 HEX、字重比、对比度阈值时,读
references/template-formulas.md。这是可选工具箱:选一个模板方向参考其参数即可,简约优先级永远高于信息密度,不要因为有模板就堆色块、堆小字。 - 用户给的是一张已有封面、问为什么没人点 / 帮我改 / 怎么提升点击率时,走
references/cover-diagnosis.md的诊断改版流程。 - 头像参考资产在
assets/bozhou-avatar-reference.jpg,规范化卡通参考在assets/bozhou-ip-canonical-cartoon-reference.png。凡是封面出现泊舟 IP,必须先用view_image打开至少一张参考图,优先两张都打开,并在系统imagegen提示词里明确写成 identity reference;不能只把 IP 特征写进文字提示词。
输出位置(重要)
封面默认存进对应视频工程文件夹,不再统一塞进 douyin-covers/。
- 确定目标视频工程:用户指定了某个工程目录就用它;否则用当前所在的视频工程(含
逐字稿.md/分镜.md/index.html等成片资产的那个项目目录);标题能明确对应到某个已有工程时也用那个工程。 - 默认只把通过检查的最终图存到该工程目录下的
cover/子文件夹(不存在就先创建),例如prompt-context-harness/cover/。生成过程中的试稿留在系统 Image Gen 默认目录,不复制进项目。 - 文件名包含标题 slug 和比例,例如
cover/harness-cover-AI客服退错旧卡-3x4.png。只有用户明确要求保留多个候选或方案时,才使用-candidate-1、-candidate-2并把候选复制进项目。 - 只有在无法判断属于哪个视频工程(例如在仓库根目录泛泛生成、与任何成片项目都无关)时,才回退到旧路径
douyin-covers/YYYY-MM-DD/generated/。 - 不确定该放进哪个工程目录、且存在多个候选工程时,先问用户一句,不要凭空选。
工具硬约束
- 小白学AI系列封面例外:如果
xiaobai-ai-coverskill 可用,停止本流程,改用该 skill 的系统内置imagegen+ 固定参考图流程。 - 默认必须使用系统
imagegenskill 的内置image_gen工具生成封面图。不要默认调用gpt-imageskill、DragonCode 脚本、第三方生图脚本或其它通用图像工具;只有用户明确要求 CLI/API/DragonCode 路径时,才另行按用户指定路径处理。 - IP/人物封面必须带参考图:先用
view_image把参考图放进上下文,再在提示词Input images中标注“identity reference”。如果做泊舟 IP,至少使用assets/bozhou-avatar-reference.jpg,优先同时使用规范化卡通参考图;不得只靠文字描述“黑发眼镜程序员”。 - 不要用代码合成封面:禁止用 Pillow、ImageMagick、Canvas、SVG、HTML/CSS 截图、程序绘图等方式生成、拼接、绘制、叠加、修补封面画面或标题文字。
- 本地命令只用于必要的非视觉操作:创建
cover/目录、复制系统 Image Gen 输出、重命名文件、读取尺寸、查看图片。 - 如果系统 Image Gen 一次生成的文字或构图不合格,解决方案是改提示词并重新调用
image_gen,而不是用代码修字、补字、换背景或做局部合成。
输入判断
从用户消息中提取:
title:封面主标题。没有标题时先问一句,不要凭空编主标题。ratio:默认3:4。用户说横版、视频封面、B 站、公众号头图、4:3 时用4:3。用户说合集封面、正方形、1:1、1080x1080、1080*1080 时用1:1。subtitle:可选,用于补充收益、冲突或系列信息。platform:默认抖音/小红书竖版封面。tone:从标题推断,可为新手入门、争议纠错、工具教程、经验总结、案例拆解、效率提升、避坑警示、方法论等。
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 173 lines · 374 tokens per session scan A 88cacb16d4de
douyin-cover is a skill published in the GitHub repository bozhouDev/video-skills-toolkit (139 stars, last pushed 1mo ago), licensed MIT. It adds 374 tokens to every session and 4,203 once invoked, about $0.0019 per session on Opus 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 2026-08-30.
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