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Youtube Toolkit

Community
wquguru
youtube-toolkit

Download YouTube videos with yt-dlp and post-process them with ffmpeg — fetch best-quality video/audio, convert formats, extract audio, and burn in translated (e.g. Chinese) subtitles with a translator watermark. Covers cross-environment tool installation (macOS-focused) including the ffmpeg-full / libass gotcha. Triggers on "youtube 视频下载处理".

Overview

Publisherwquguru
Repositoryskills
Skill nameyoutube-toolkit
Stars
94
Forks
7
Bundled files
4
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by wquguru on GitHub. Read the source before you install it.

Installation

Install the Youtube Toolkit AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/wquguru/skills/tree/main/skills/youtube-toolkit
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/wquguru/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/youtube-toolkit .claude/skills/youtube-toolkit
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Youtube Toolkit in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Youtube Toolkit on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Youtube Toolkit is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

YouTube Toolkit

Download and process YouTube videos: grab best-quality streams, convert/extract, and burn in translated subtitles + a watermark. macOS-first, with Linux notes.

Two helper scripts do the deterministic work; the agent does the judgement work (choosing formats, translating subtitles). Read the relevant references/ file before a non-trivial task instead of guessing flags.

⚠️ Pick the right ffmpeg first (the #1 gotcha)

Homebrew's lean ffmpeg formula ships without libass/libfreetype, so it has no subtitles and no drawtext filter — subtitle burn-in and watermarks fail with No option name / Error parsing filterchain. Verify before relying on it:

bash
ffmpeg -hide_banner -filters 2>/dev/null | grep -E ' subtitles | drawtext ' || echo "NO subtitle/drawtext support"

If missing, install the full build (keg-only, does not touch your ffmpeg):

bash
brew install ffmpeg-full     # binary at /opt/homebrew/opt/ffmpeg-full/bin/ffmpeg

scripts/burn-subs.sh auto-detects an ffmpeg with libass, preferring ffmpeg-full. Plain download/convert work fine with the lean ffmpeg.

Install tools

One shot: bash scripts/install-tools.sh (detects OS; installs yt-dlp, an ffmpeg with libass, and optionally the deno JS runtime). Or do it manually — details and Linux/conda variants in references/installation-and-recipes.md.

yt-dlp prints No supported JavaScript runtime and falls back to the Android client. It usually still works; install deno (brew install deno) to silence it and unlock all formats.

Common tasks

Download (best quality)

bash
yt-dlp -o "~/Downloads/%(title)s [%(id)s].%(ext)s" "<URL>"

Best video+audio merge to mp4, audio-only mp3, playlists, cookies, sections — see the recipes in references/installation-and-recipes.md.

Convert / extract

Re-encode webm (often AV1+Opus, not universally playable) to H.264+AAC mp4:

bash
ffmpeg -i in.webm -c:v libx264 -crf 20 -preset medium -c:a aac -b:a 192k -movflags +faststart out.mp4

More recipes (remux without re-encode, trim, extract audio) in references.

Burn in translated subtitles + watermark ← marquee workflow

Produces a hard-subbed mp4 with a translator watermark (e.g. @handle 翻译). Full detail in references/translate-and-burn.md; the loop is:

  1. List + fetch source subtitles (translate from the original language, not YouTube's machine-translated track, for quality worthy of a translator credit):
    bash
    yt-dlp --list-subs --skip-download "<URL>"
    yt-dlp --write-auto-subs --sub-langs en --convert-subs srt --skip-download -o "subs_%(id)s.%(ext)s" "<URL>"
  2. Re-segment + translate. YouTube auto-captions are word-by-word rolling cues with overlapping timestamps — burning them as-is double-stacks lines. Re-segment into whole sentences (start = first cue's start, end = next sentence's start) and translate each into a clean .zh.srt. The agent does this; see references/translate-and-burn.md for the method.
  3. Burn it in:
    bash
    bash scripts/burn-subs.sh -i in.webm -s subs_ID.zh.srt -w "@handle 翻译" -o out_zh.mp4
    Encode from the highest-quality source (the original webm), not an already-compressed mp4, to avoid a second generation loss. Preview a single frame first (-copyts -ss T … -frames:v 1, see references) before the full run.

Gotchas (learned the hard way)

SymptomCause → Fix
No option name / filterchain parse error on -vf subtitles=…Lean Homebrew ffmpeg lacks libass → use ffmpeg-full
force_style='…,…' breaks -vf parsingCommas in force_style confuse the parser → convert SRT→ASS and edit the Style: line instead (what burn-subs.sh does)
Two subtitle lines stack / overlapSource is rolling auto-captions → re-segment into non-overlapping sentences
Subtitle missing in preview frame-ss before -i resets PTS → add -copyts for preview seeks
AV1+Opus .mp4 won't play in QuickTimeRe-encode to H.264+AAC (+faststart)
Chinese subtitles render as boxesPick a CJK font; macOS has Hiragino Sans GB.ttc, STHeiti *.ttc, Songti.ttc, Arial Unicode.ttf (no PingFang.ttc at the legacy path)

References

  • references/installation-and-recipes.md — cross-env install (brew/pip/conda/apt), yt-dlp & ffmpeg recipe cookbook.
  • references/translate-and-burn.md — subtitle re-segmentation, translation, ASS styling, preview/encode details.
  • scripts/install-tools.sh — installs yt-dlp + libass-enabled ffmpeg (+ optional deno).
  • scripts/burn-subs.sh — burns an SRT/ASS subtitle + optional watermark into a video.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Youtube Toolkit AI skill do?

Download YouTube videos with yt-dlp and post-process them with ffmpeg — fetch best-quality video/audio, convert formats, extract audio, and burn in translated (e.g. Chinese) subtitles with a translator watermark. Covers cross-environment tool installation (macOS-focused) including the ffmpeg-full / libass gotcha. Triggers on "youtube 视频下载处理".

Why use Youtube Toolkit on TypingMind?

Because you install it once and use it with any model. Youtube Toolkit is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Youtube Toolkit in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/wquguru/skills/tree/main/skills/youtube-toolkit. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Youtube Toolkit?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Youtube Toolkit?

As many as you like. As long as a model supports skills, you can use Youtube Toolkit with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Youtube Toolkit AI skill free?

Yes. It is published on GitHub by wquguru under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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