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📦 Ingest Youtube

ingest-youtube

YouTube動画の字幕を自動で取得し

⏱ 手作業のあれこれ 1日 → 1時間

📺 まず動画で見る(YouTube)

▶ 【Claude Code完全入門】誰でも使える/Skills活用法/経営者こそ使うべき ↗

※ jpskill.com 編集部が参考用に選んだ動画です。動画の内容と Skill の挙動は厳密には一致しないことがあります。

📜 元の英語説明(参考)

Pull a YouTube video transcript into a queryable markdown vault with yt-dlp subtitle discovery, VTT cleanup, metadata frontmatter, and capture-seed stubs.

🇯🇵 日本人クリエイター向け解説

一言でいうと

YouTube動画の字幕を自動で取得し

※ jpskill.com 編集部が日本のビジネス現場向けに補足した解説です。Skill本体の挙動とは独立した参考情報です。

⚠️ ダウンロード・利用は自己責任でお願いします。当サイトは内容・動作・安全性について責任を負いません。

🎯 このSkillでできること

下記の説明文を読むと、このSkillがあなたに何をしてくれるかが分かります。Claudeにこの分野の依頼をすると、自動で発動します。

📦 インストール方法 (3ステップ)

  1. 1. 上の「ダウンロード」ボタンを押して .skill ファイルを取得
  2. 2. ファイル名の拡張子を .skill から .zip に変えて展開(macは自動展開可)
  3. 3. 展開してできたフォルダを、ホームフォルダの .claude/skills/ に置く
    • · macOS / Linux: ~/.claude/skills/
    • · Windows: %USERPROFILE%\.claude\skills\

Claude Code を再起動すれば完了。「このSkillを使って…」と話しかけなくても、関連する依頼で自動的に呼び出されます。

詳しい使い方ガイドを見る →
最終更新
2026-05-17
取得日時
2026-05-17
同梱ファイル
1

💬 こう話しかけるだけ — サンプルプロンプト

  • Ingest Youtube の使い方を教えて
  • Ingest Youtube で何ができるか具体例で見せて
  • Ingest Youtube を初めて使う人向けにステップを案内して

これをClaude Code に貼るだけで、このSkillが自動発動します。

📖 Claude が読む原文 SKILL.md(中身を展開)

この本文は AI(Claude)が読むための原文(英語または中国語)です。日本語訳は順次追加中。

ingest-youtube — YouTube-to-vault connector

Pulls YouTube transcripts into a markdown vault as queryable typed-memory entries that downstream skills (knowledge graph extraction, voice-fingerprint training, content repurposing, action-item extraction) can act on.

Same pattern as ingest-slack, ingest-whatsapp, ingest-notion, ingest-linear, ingest-github, ingest-gmail. Adding YouTube means a new normalizer, not a new architecture.

When to use

  • User pastes a YouTube URL and asks for a transcript or summary
  • User says /ingest-youtube <url> for a single video
  • User asks to capture, sync, ingest, transcribe, or pull a talk/podcast/keynote into the vault

Do NOT use for:

  • Downloading the actual video file (use yt-dlp directly with -f best)
  • Channel-wide ingestion or --days windows; this script ingests one video URL at a time
  • Live streams (transcripts are not stable)
  • Non-YouTube sources (Vimeo, Twitch, Twitter Spaces have their own connectors)
  • One-off transcript reads where the user does not want a vault file (run yt-dlp --write-auto-sub directly and pipe to stdout)

How it works

  1. Parse the input as one YouTube video URL.
  2. Verify yt-dlp is installed. If not, the script exits with install instructions: brew install yt-dlp (macOS) or pip3 install --user yt-dlp.
  3. Call yt-dlp --list-subs <url> to enumerate available subtitles.
  4. Subtitle priority: manual subs > auto-generated captions. Manual subs preserve creator-provided punctuation and speaker labels; auto-gen is uppercase + no punctuation.
  5. Download the highest-priority subtitle as VTT via yt-dlp --write-sub --sub-lang <lang> --skip-download. Default language preference: en,es (English first, Spanish second).
  6. Strip VTT timing markers and merge into clean prose paragraphs. Deduplicate repeated lines (auto-generated VTTs are line-doubled). Preserve speaker labels if the source had them.
  7. Pull video metadata (title, channel, upload date, duration, video_id, URL) via yt-dlp --print-json --skip-download.
  8. Slugify the channel name and video title. Write to External Inputs/YouTube/<channel-slug>/<YYYY-MM-DD>-<video-slug>.md.
  9. Scan transcript for trigger keywords (decision, framework, model, principle, "the lesson is", playbook, anti-pattern, case study). For each match, create a writing-seed stub at Meta/Captures/<YYYY-MM-DD>-youtube-<channel-slug>-<video-id>.md so the seed lands in the captures aggregator.
  10. Print summary: file path, transcript word count, language, seeds detected.

Invocation

python3 ingest.py <youtube-url> [--vault <path>] [--lang <code>]

Defaults:

  • --vault: $VAULT_ROOT env var or current directory
  • --lang: en,es (English first, Spanish second; matches a common bilingual default)
  • --whisper: accepted as a future fallback flag, but this version writes a stub when no subtitles are available

Output contract

The vault file at External Inputs/YouTube/<channel-slug>/<YYYY-MM-DD>-<video-slug>.md has frontmatter:

---
type: external-input
source: youtube
video_id: <11-char ID>
url: https://www.youtube.com/watch?v=<id>
channel: <channel-name>
channel_url: https://www.youtube.com/<handle>
title: <video title>
upload_date: <YYYY-MM-DD>
duration_seconds: <int>
language: <ISO code>
subtitle_source: manual | auto | whisper
word_count: <int>
ingested_at: <ISO 8601 timestamp>
---

Body is the cleaned transcript as paragraph prose. If the source had speaker labels, format as **<speaker>:** <text> per turn.

Idempotency

Re-ingesting the same video URL overwrites the same vault file. The seed stub filenames hash the video_id, so the same source video produces the same stub filename across re-runs. Re-runs refresh, never duplicate.

Missing subtitles

If yt-dlp --list-subs returns no manual or auto subtitles, the script writes a stub vault note with the video metadata and source URL instead of failing silently. The --whisper flag is reserved for a future local transcription fallback and currently reports that the fallback is not implemented.

For a manual fallback today, download audio with yt-dlp, transcribe it with your local Whisper workflow, and add captions or transcript text before rerunning the ingest.

Limitations

  • Ingests one YouTube video URL per run; channel handles, playlists, and --days windows are out of scope.
  • Depends on subtitles returned by yt-dlp; videos without subtitles produce a metadata stub, not a transcript.
  • Does not download video files or perform built-in Whisper transcription in this version.
  • Network availability, YouTube subtitle access, and local yt-dlp behavior determine whether ingest succeeds.

Acceptance test

Run against the first YouTube video ever uploaded:

python3 ingest.py "https://www.youtube.com/watch?v=jNQXAC9IVRw" --vault /tmp/test

Expected output:

Wrote 39 words to /tmp/test/External Inputs/YouTube/jawed/2005-04-24-me-at-the-zoo.md. Language: en. Subtitle source: manual.

The output file contains valid frontmatter and a clean prose body.

Dependencies

  • yt-dlp (required): install via brew install yt-dlp or pip3 install --user yt-dlp
  • whisper-cpp (optional for a manual fallback outside this script)

Source

Bundled in adelaidasofia/ai-brain-starter, a verification harness around an AI agent so memory compounds instead of corrupts. The skill is part of the ingest-* family of vault connectors.