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 yanhua1010/self-media-content-workflow --skill self-media-short-videogit clone --depth 1 https://github.com/yanhua1010/self-media-content-workflowWrote 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/yanhua1010/self-media-content-workflow/self-media-short-video)<a href="https://agentmods.dev/skills/yanhua1010/self-media-content-workflow/self-media-short-video"><img src="https://agentmods.dev/badge/skills/yanhua1010/self-media-content-workflow/self-media-short-video/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/yanhua1010/self-media-content-workflow/self-media-short-video"><img src="https://agentmods.dev/badge/skills/yanhua1010/self-media-content-workflow/self-media-short-video.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 | $0.00158 | $0.01479 |
| Opus 5.5 | $0.00063 | $0.00592 |
| Sonnet 5.5 | $0.00032 | $0.00296 |
| Haiku 4.5 | $0.00016 | $0.00148 |
Grade A, and why
self-media-short-video 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 17d 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
短视频与视频制片
原则
- 一条视频只讲一个核心判断。
- 前 3 秒给出冲突、结果、利益或具体场景；优先用第二人称（“你……”）或一句能重复出现的母题句把观众拉进来。
- 字幕必须能脱离声音独立成立：关掉声音只看字幕也能看懂。
- 口播必须说得出口，不把长文章切成字幕。
- 画面承担证明、演示、对比或情绪任务，不重复字幕。
- 优先使用真实人物声音、产品录屏和真实证据，不默认数字人或动画。
- 数字人是用户主动选择后的制片模式，必须有头像与声音的使用权利；用户本人负责在所选数字人平台中手动上传、创建和选定敏感素材，并保留人工预览和发布确认。
确认输入
检查：目标平台、受众、内容目标、时长、出镜方式、可用素材、核心判断、行动和不能展示的内容。缺少会改变方案的信息时最多问 3 个问题。
视频制作模式
方案模式：没有原片、没有确认数字人平台素材已就绪，或没有明确成片授权时，交付可拍摄方案，不擅自生成成片。真人剪辑模式：用户提供原片并明确要求剪辑时，调用当前环境可用的视频、字幕和音频能力。数字人制片模式：用户明确选择数字人、确认肖像与声音权利，并已在所选平台手动上传、创建和选定数字人及声音后，按 digital-human-production.md 生成数字人讲解片段，再完成画面解析、字幕、人物窗口和竖屏成片。动画解说制片模式：用户明确要无真人出镜的动画成片，且运行时发现了配音、图像和视频合成能力时，按 animated-explainer-production.md 和 explainer-narrative.md 完成叙事骨架、合成配音、画面素材、镜头合成、配乐授权与混音，先出主版本。
动画解说模式同样由运行时发现工具：可以是已安装的动画制片 Skill、剪辑软件工程模板或用户指定的视频工具，核心流程不写死某家图像或配音服务。付费生成前向用户说明预估费用。
数字人模式的生成工具由运行时发现。若当前环境提供 Topview MCP，可在用户确认 Topview 中的数字人和声音已就绪后，将其作为数字人片段生成适配器；本 Skill 不调用上传凭证或克隆接口代替用户上传原始头像、录音。核心流程不写死供应商 API。生成能力或合成能力不可用时，降级为数字人分镜、画面映射、字幕稿、素材清单和可手动完成的发布包。
多平台版本
成片要发往多个平台时，先确定主版本（YouTube 通常是 16:9，竖屏平台通常是 9:16），再按 video-platform-versions.md 派生其他版本：横屏转竖屏（原生重排或横转竖包装）、烧录字幕或 SRT、各平台封面、AI 标识和配乐署名。用 video-release-matrix-template.md 记录每个版本和发布字段。
结构
选择一种主体结构：
- 问题 → 方法 → 例证。
- 结果 → 过程 → 教训。
- 冲突 → 选择 → 后果。
- 演示 → 解释 → 适用边界。
结尾给一个记忆点和一个主要行动。
分镜
使用 storyboard-template.md。每个镜头写清：
- 时间和时长。
- 景别、画面、人物动作或录屏操作。
- 口播、字幕和屏幕文字。
- 证据、B-roll、音效、BGM 和转场。
所有镜头时长之和必须等于目标时长。字幕与口播事实必须一致。
输出包
交付：
- 3 个钩子和推荐版本。
- 完整口播稿。
- 分镜表或录屏清单。
- 字幕稿。
- 封面标题和画面说明。
- 发布标题、正文、话题和 BGM 建议。
- 拍摄或素材缺口。
数字人制片模式额外交付：肖像与声音权利确认、平台手动上传和素材就绪状态、数字人生成片段、画面解析与人物窗口规格、字幕文件或字幕文本、发音词表、最终视频技术规格、AI/数字人披露要求和验收结果。交付包不包含原始头像、录音或平台私有标识。
动画解说制片模式额外交付：主版本和各平台派生版本、字幕文件、各平台封面、配乐授权与署名文本、发音词表、事实来源清单、响度与画幅等技术规格、制片工程目录和重建命令。
多平台发布时交付发布矩阵；上传和发布交给 self-media-video-publisher，并遵守逐平台授权。
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.
- 17d ago Changed · +1 lines edf474f331e2
- 25d ago Changed · +11 lines · +40 tokens per session 8887ee9b0383
- 1mo ago First seen · 66 lines · 118 tokens per session scan A 2bad4ca4dda8
self-media-short-video is a skill published in the GitHub repository yanhua1010/self-media-content-workflow (626 stars, last pushed 14d ago), licensed MIT. It adds 158 tokens to every session and 1,479 once invoked, about $0.0006 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 2026-08-30.
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