Yt Dlp Expert

yt-dlpを使用した動画ダウンロードの専門スキル。YouTube、ニコニコ動画、Twitter/X、TikTok等1000以上のサイトから動画・音声・字幕をダウンロード。フォーマット選択、プレイリスト処理、メタデータ抽出を効率的に支援。Use when downloading videos, extracting audio, getting subtitles, or fetching metadata from YouTube and other video sites.

No API Required

Download Skill Package (.skill) View Source on GitHub

Table of Contents

1. Overview

yt-dlp Expert

2. Prerequisites

  • API Key: None required
  • Python 3.9+ recommended

3. Quick Start

Invoke this skill by describing your analysis needs to Claude.

4. How It Works

Follow the skill’s SKILL.md workflow step by step, starting from a small validated input.

5. Usage Examples

  • Use Yt Dlp Expert when you need a structured workflow rather than an ad-hoc answer.
  • Start with a small representative input before applying the workflow to production data or assets.
  • Review the helper scripts and reference guides to tailor the output format to your project.

6. Understanding the Output

  • A structured response or artifact aligned to the skill’s workflow.
  • Reference support from 3 guide file(s).
  • Reusable output that can be reviewed, refined, and incorporated into a wider project workflow.

7. Tips & Best Practices

  • Begin with the smallest realistic sample input so you can validate the workflow before scaling up.
  • Keep skills/yt-dlp-expert/SKILL.md open while working; it remains the authoritative source for the full procedure.
  • Review the most relevant reference files first instead of scanning every guide: authentication.md, download_options.md, subtitle_extraction.md.
  • Preserve intermediate outputs so you can explain assumptions, diffs, and follow-up actions clearly.

8. Combining with Other Skills

  • Combine this skill with adjacent skills in the same category when the work spans planning, implementation, and review.
  • Browse the broader category for neighboring workflows: category index.
  • Use the English skill catalog when you need to chain this workflow into a larger end-to-end process.

9. Troubleshooting

  • Re-check prerequisites first: missing runtime dependencies and unsupported file formats are the most common failures.
  • If a helper script is involved, run it with a minimal sample input before applying it to a full dataset or repository.
  • Compare your input shape against the reference files to confirm expected fields, sections, or metadata are present.
  • Confirm the expected Python version and required packages are installed in the active environment.

10. Reference

References:

  • skills/yt-dlp-expert/references/authentication.md
  • skills/yt-dlp-expert/references/download_options.md
  • skills/yt-dlp-expert/references/subtitle_extraction.md