Create timestamped chapter lists for medium-length and long videos. Transcribe speech with timing information, identify topic changes, and name each chapter, producing a text table of contents for YouTube or B站 descriptions plus structured JSON.
视频章节 / 时间戳目录：给中长视频自动生成章节划分和时间戳目录，用于 B站分P/YouTube 章节/视频描述区，方便观众跳转、提升完播。当用户说 视频章节、章节目录、时间戳、分章节、视频目录、chapters、B站章节、YouTube 章节、给视频加时间点、看点目录、视频大纲时间戳 时使用。
编排复用 asr.py（带时间轴转录），章节划分与命名由 LLM 完成。与 video-to-article 区别：那个把视频改写成成篇图文，本 SKILL 只出章节时间戳目录。
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See how to installReview the instructions the agent will receive before you install.
给中长视频生成章节时间戳目录（B站/YouTube 描述区可用）。带时间轴转录走
asr.py， 章节切分与命名由你（LLM）完成。
出成篇图文见 video-to-article；出字幕见 auto-subtitle；切成短视频见 video-highlights。
| 字段 | 必填 | 说明 |
|---|---|---|
| 视频文件 | 是 | 中长视频（教程/评测/讲座/直播回放；没给就问） |
| 目标平台 | 否 | B站 / YouTube / 通用（影响格式与措辞） |
| 章节数 | 否 | 期望章节数（默认按内容自然划分，通常 5-12 段） |
outputs/主题名/）chapters.txt — 时间戳目录（每行 mm:ss 章节名，可直接贴描述区）chapters.json — 结构化（start 秒 + 标题），供程序化使用transcript.txt — 转录原文（备查）脚本路径（相对项目根）：skills/shared/scripts/asr.py。
python skills/shared/scripts/asr.py transcribe -i <视频> --format json \
-o outputs/主题名/transcript.json
（首次跑 ASR 需外网代理下模型，见 auto-subtitle 前置说明。）
读 transcript.json（每段带 start/end），按话题转折划分章节：
写 chapters.txt（每行 mm:ss 章节名，首行必须 00:00）：
00:00 开场｜今天聊什么
01:24 第一个坑：xxx
03:50 实测环节
...
同时写 chapters.json：[{"start": 0, "title": "开场｜今天聊什么"}, ...]。
0:00，≥3 章、每章 ≥10s 自动生效。mm:ss 标题。chapters.txt 通用可读。outputs/主题名/。章节时间戳是 YouTube/B站 提升完播与检索的标准做法（首章 0:00、≥10s 间隔为平台硬规则）。 转录用 faster-whisper（asr.py）出时间轴，话题切分交给 LLM——确定性 IO 与语义划分分层。
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