How do I install the Youtube Archiver skill?

Run npx skillmds add modbender/youtube-archiver in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Youtube Archiver safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: executes scripts. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Youtube Archiver?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Youtube Archiver free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Youtube Archiver?

modbender (@modbender) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Youtube Archiver by modbender — Agent Skill

Name: Youtube Archiver
Rating: 4.2 (5 reviews)
Author: modbender

Youtube Archiver

Archive YouTube playlists into markdown notes with metadata, transcripts, AI summaries, and tags. Use when a user asks to import/sync YouTube playlists, archive Watch Later or Liked videos, enrich YouTube notes, batch process video notes, or automate recurring YouTube-to-markdown sync jobs with cron.

modbender 0db78c4 8 files · 75.6 KB Updated Sep 9, 2026 12 repo stars

File contents

YouTube Archiver

Use this skill to import YouTube playlists into markdown files and optionally enrich notes with transcript, summary, and tagging.

Requirements

Python 3.7+
yt-dlp (pip install yt-dlp or brew install yt-dlp)
A browser signed into YouTube (for private playlists like Liked/Watch Later)
macOS: terminal needs Full Disk Access to read browser cookies
Windows: browser cookie extraction can be flaky; cookies_file export is the safer path
Linux: works on desktop installs; headless servers need cookies_file

First-run setup flow (interactive)

If no config exists at <output>/.config.json, ask these questions before running scripts.

Required questions

Where should archived notes be stored?
- Default: ./YouTube-Archive
Which playlists should be archived?
- Accept playlist IDs or URLs
- Default: LL (Liked Videos), WL (Watch Later)
Which browser is signed into YouTube for cookie auth?
- Default: chrome

Optional enrichment questions

Ask only if the user wants summaries/tags.

Generate AI summaries? (yes/no)
Summary provider? (openai, gemini, anthropic, openrouter, ollama, none)
Summary model name?
API key env var name?
Enable auto-tagging? (yes/no)
Tagging provider/model/env var?
Keep default tags or define custom vocabulary?

First-run execution sequence

Run init:
- python3 <skill>/scripts/yt-import.py --output <output-dir> --init
Edit <output-dir>/.config.json from the user’s answers.
Verify auth with dry run:
- python3 <skill>/scripts/yt-import.py --output <output-dir> --dry-run
Run real import.
Run enrichment (optional):
- python3 <skill>/scripts/yt-enrich.py --output <output-dir> --limit 10

One-shot quick start

Use this for immediate manual sync:

python3 <skill>/scripts/yt-import.py --output <output-dir>
python3 <skill>/scripts/yt-enrich.py --output <output-dir> --limit 10

Useful import flags:

--dry-run
--playlist <ID> (repeatable)
--no-summary
--no-tags
--cookies <path/to/cookies.txt>
--browser <name>

Useful enrich flags:

--dry-run
--limit <N>
--strict-config

Idempotency and safety behavior

Import skips already archived videos by video_id.
Filenames include video ID: Title [video_id].md.
Enrichment skips notes where frontmatter has enriched: true.
Lockfile prevents concurrent runs: <output-dir>/.yt-archiver.lock.

Automation with cron (single-agent default)

Offer cron only after one successful manual run.

Example schedule (daily 11:00):

Import new videos
Enrich a bounded batch

Example task text:

Run yt-import.py for <output-dir>, then run yt-enrich.py --limit 10 for the same output.

Keep it single-agent by default. Do not assume multi-agent routing.

Troubleshooting and provider details

Read these references when needed:

Provider setup, model suggestions, cost: references/providers.md
Common failures and fixes: references/troubleshooting.md
Default summary prompt template: references/default-summary-prompt.md

---name: youtube-archiverdescription: Archive YouTube playlists into markdown notes with metadata, transcripts, AI summaries, and tags. Use when a user asks to import/sync YouTube playlists, archive Watch Later or Liked videos, enrich YouTube notes, batch process video notes, or automate recurring YouTube-to-markdown sync jobs with cron.--- # YouTube Archiver Use this skill to import YouTube playlists into markdown files and optionally enrich notes with transcript, summary, and tagging. ## Requirements - Python 3.7+ - `yt-dlp` (`pip install yt-dlp` or `brew install yt-dlp`) - A browser signed into YouTube (for private playlists like Liked/Watch Later) - **macOS**: terminal needs Full Disk Access to read browser cookies - **Windows**: browser cookie extraction can be flaky; `cookies_file` export is the safer path - **Linux**: works on desktop installs; headless servers need `cookies_file` ## First-run setup flow (interactive) If no config exists at `<output>/.config.json`, ask these questions before running scripts. ### Required questions 1. Where should archived notes be stored? - Default: `./YouTube-Archive` 2. Which playlists should be archived? - Accept playlist IDs or URLs - Default: `LL` (Liked Videos), `WL` (Watch Later) 3. Which browser is signed into YouTube for cookie auth? - Default: `chrome` ### Optional enrichment questions Ask only if the user wants summaries/tags. 1. Generate AI summaries? (yes/no) 2. Summary provider? (`openai`, `gemini`, `anthropic`, `openrouter`, `ollama`, `none`) 3. Summary model name? 4. API key env var name? 5. Enable auto-tagging? (yes/no) 6. Tagging provider/model/env var? 7. Keep default tags or define custom vocabulary? ## First-run execution sequence 1. Run init: - `python3 <skill>/scripts/yt-import.py --output <output-dir> --init` 2. Edit `<output-dir>/.config.json` from the user’s answers. 3. Verify auth with dry run: - `python3 <skill>/scripts/yt-import.py --output <output-dir> --dry-run` 4. Run real import. 5. Run enrichment (optional): - `python3 <skill>/scripts/yt-enrich.py --output <output-dir> --limit 10` ## One-shot quick start Use this for immediate manual sync: ```bash python3 <skill>/scripts/yt-import.py --output <output-dir> python3 <skill>/scripts/yt-enrich.py --output <output-dir> --limit 10 ``` Useful import flags: - `--dry-run` - `--playlist <ID>` (repeatable) - `--no-summary` - `--no-tags` - `--cookies <path/to/cookies.txt>` - `--browser <name>` Useful enrich flags: - `--dry-run` - `--limit <N>` - `--strict-config` ## Idempotency and safety behavior - Import skips already archived videos by `video_id`. - Filenames include video ID: `Title [video_id].md`. - Enrichment skips notes where frontmatter has `enriched: true`. - Lockfile prevents concurrent runs: `<output-dir>/.yt-archiver.lock`. ## Automation with cron (single-agent default) Offer cron only after one successful manual run. Example schedule (daily 11:00): 1. Import new videos 2. Enrich a bounded batch Example task text: - `Run yt-import.py for <output-dir>, then run yt-enrich.py --limit 10 for the same output.` Keep it single-agent by default. Do not assume multi-agent routing. ## Troubleshooting and provider details Read these references when needed: - Provider setup, model suggestions, cost: `references/providers.md` - Common failures and fixes: `references/troubleshooting.md` - Default summary prompt template: `references/default-summary-prompt.md`

Frequently asked questions