ingest-youtube
Pull a YouTube video transcript into a queryable markdown vault with yt-dlp subtitle discovery, VTT cleanup, metadata frontmatter, and capture-seed stubs.
Best use case
ingest-youtube is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Pull a YouTube video transcript into a queryable markdown vault with yt-dlp subtitle discovery, VTT cleanup, metadata frontmatter, and capture-seed stubs.
Teams using ingest-youtube should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/ingest-youtube/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How ingest-youtube Compares
| Feature / Agent | ingest-youtube | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Pull a YouTube video transcript into a queryable markdown vault with yt-dlp subtitle discovery, VTT cleanup, metadata frontmatter, and capture-seed stubs.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
SKILL.md Source
# 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 ```bash 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: ```yaml --- 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: ```bash 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](https://github.com/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.
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