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YouTube 提文案

该 Skill 采用“字幕优先”流程:先运行 Python 脚本结合 yt-dlp 抓取视频元数据与字幕,再读取 summary.json 和转录文本,由模型输出中文摘要、翻译、带时间戳的要点与问答;无字幕时提示需要语音转文字方案,必要时用 ffmpeg 抽帧做视觉补充。

benheee
benheee
热度 14.42
最近更新 2026-07-23 17:56:57
分类:效率依赖:代码执行 / 读写文件 / 第三方 API / 内部调用大模型应用场景:摘要总结 / 翻译 / 研究

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add youtube-digest
Metadata
name
youtube-digest
description
Understand, summarize, translate, and extract key points from YouTube videos. Use when a user provides a YouTube URL and wants: (1) a Chinese summary, (2) a transcript or subtitle extraction, (3) translation of spoken content, (4) timestamps / chapter notes, (5) visual understanding via key frames, or (6) question answering about a video. Prefer this skill for transcript-first workflows.

YouTube Digest

Use a transcript-first workflow.

Quick workflow

  1. Run scripts/fetch_youtube.py <url> --out <dir> to collect metadata and subtitles. If behind a proxy, add --proxy <proxy-url>.
  2. If subtitles exist, read summary.json and the generated transcript file first.
  3. If the user only wants a quick answer, summarize directly from the transcript.
  4. If the user needs stronger visual grounding, extract key frames with ffmpeg after downloading the video or by using an existing local video file.
  5. If no subtitles are available, report that transcript extraction needs yt-dlp + a speech-to-text path (for example Whisper) before promising a result.

Default behavior

  • Prefer manual subtitles over auto subtitles.
  • Prefer Chinese subtitles when available; otherwise use English auto/manual subtitles.
  • Keep downloads minimal: subtitles + metadata first, full video only when visual analysis is necessary.
  • For long videos, produce:
    • 3-line executive summary
    • bullet timeline with timestamps
    • key insights / actionable points
    • open questions or uncertainties

Outputs

For normal requests, return:

  • Video topic
  • Summary (in user's language)
  • Key timestamps
  • Notable quotes / insights
  • If confidence is limited, say whether the result came from manual subtitles, auto subtitles, or partial metadata only.

Files produced by the script

The fetch script writes an output directory containing:

  • summary.json — chosen subtitle file, title, uploader, duration, and extraction status
  • transcript.txt — plain text transcript when subtitles are available
  • raw subtitle files from yt-dlp (VTT/SRT)

Read summary.json first to decide what to do next.

Required runtime tools

  • yt-dlp for metadata + subtitle extraction
  • deno as JS runtime (required by yt-dlp 2026+)
  • ffmpeg for media conversion / optional frame extraction (optional)

Key commands

Basic extraction:

python3 scripts/fetch_youtube.py "<youtube-url>" --out /tmp/youtube-digest

With proxy:

python3 scripts/fetch_youtube.py "<youtube-url>" --proxy http://your-proxy:port --out /tmp/youtube-digest

Prefer specific subtitle languages:

python3 scripts/fetch_youtube.py "<youtube-url>" --langs zh.*,en.* --out /tmp/youtube-digest

Failure handling

  • If yt-dlp is missing, stop and install it instead of improvising.
  • If YouTube blocks the request (429 or bot detection), try using a proxy or report the limitation.
  • If only metadata is available, do not pretend you understood the full video.
  • If subtitles are auto-generated, mention that wording may be noisy.

References

  • Read references/install-and-deploy.md for deployment instructions.
  • Read references/usage-patterns.md for output templates for summaries, translations, or Q&A.