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Web scraping48k · #3336

ingest-youtube

Lets your agent download YouTube video subtitles. It organizes the text and video information to make searching easier.

What it does

This tool takes the transcript from a YouTube video and saves it into an organized text file. This allows you to easily search and use the video's content later.

When to use it

  • ✓When you find an interesting YouTube video and want to save what was said.
  • ✓When you need the video's text for studying or creating something new.
  • ✓When you want to turn a video into a text file for your personal knowledge collection.

Example of what to ask your AI

“Save the transcript for this YouTube video for me: [Video URL]”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/sickn33/agentic-awesome-skills/blob/main/plugins/agentic-awesome-skills-claude/skills/ingest-youtube/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/sickn33/agentic-awesome-skills/blob/main/plugins/agentic-awesome-skills-claude/skills/ingest-youtube/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

The tool uses a program called 'yt-dlp' to download the spoken text from the video. It cleans up this text, adds information about the video (like title and date), and saves it into a file for you.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add sickn33/agentic-awesome-skills --skill ingest-youtube

Or download just the file:

curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/ingest-youtube/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

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. Validate the URL as a single http(s) YouTube video and call yt-dlp --ignore-config --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.

…

FAQ

What if the video doesn't have subtitles?

If no subtitles are available, the tool will save only basic video information like the title and link, instead of the full text.

Can I download the whole video?

No, this tool focuses only on downloading the text (transcript) of the video, not the video file itself.

Does it work for any YouTube video?

Yes, as long as it's a single video link and has subtitles available (manual or automatic).

Details

Original description by the author

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

repo: sickn33/agentic-awesome-skills

Popularity

GitHub stars
48k
Ranking position
#3336
License
MIT
Updated
10/15/2026

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