Ingest youtube

Skill ranbot-ai/awesome-skills/skills/ingest-youtube

Awesome Claude Skills, Tools for Customizing Claude AI workflows

Install

npx -y skills add ranbot-ai/awesome-skills --skill ingest-youtube

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
6 stars6 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

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

SKILL.md

5.3 KB, ~1.2k tokens by cl100k_base, as published. Nobody here has run it

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

Parse the input as one YouTube video URL.
Verify yt-dlp is installed. If not, the script exits with install instructions: brew install yt-dlp (macOS) or pip3 install --user yt-dlp.
Validate the URL as a single http(s) YouTube video and call yt-dlp --ignore-config --list-subs -- <url> to enumerate available subtitles.
Subtitle priority: manual subs > auto-generated captions. Manual subs preserve creator-provided punctuation and speaker labels; auto-gen is uppercase + no punctuation.
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).
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.
Pull video metadata (title, channel, upload date, duration, video_id, URL) via yt-dlp --print-json --skip-download.
Slugify the channel name and video title. Write to External Inputs/YouTube/<channel-slug>/<YYYY-MM-DD>-<video-slug>.md.
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.
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 In