Tencent SkillHub · Developer Tools

TubeScribe

YouTube video summarizer with speaker detection, formatted documents, and audio output. Works out of the box with macOS built-in TTS. Optional recommended tools (pandoc, ffmpeg, mlx-audio) enhance quality. Requires internet for YouTube access. No paid APIs or subscriptions. Use when user sends a YouTube URL or asks to summarize/transcribe a YouTube video.

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Requirements

Target platform: OpenClaw
Install method: Manual import
Extraction: Extract archive
Prerequisites: OpenClaw
Primary doc: SKILL.md

Package facts

Download mode: Manual review
Package format: ZIP package
Source platform: Tencent SkillHub
What's included: CHANGELOG.md, README.md, SKILL.md, scripts/config.py, scripts/html_writer.py, scripts/setup.py

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Release facts

Source: Tencent SkillHub
Verification: Indexed source record
Version: 1.1.8

Provenance

Publisher: matusvojtek
Source page: View original listing
Canonical URL: Open canonical page

Documentation

ClawHub primary doc Primary doc: SKILL.md 33 sections Open source page

TubeScribe 🎬

Turn any YouTube video into a polished document + audio summary. Drop a YouTube link → get a beautiful transcript with speaker labels, key quotes, timestamps that link back to the video, and an audio summary you can listen to on the go.

💸 Free & No Paid APIs

No subscriptions or API keys — works out of the box Local processing — transcription, speaker detection, and TTS run on your machine Network access — fetching from YouTube (captions, metadata, comments) requires internet No data uploaded — nothing is sent to external services; all processing stays on your machine Safe sub-agent — spawned sub-agent has strict instructions: no software installation, no network calls beyond YouTube

✨ Features

📄 Transcript with summary and key quotes — Export as DOCX, HTML, or Markdown 🎯 Smart Speaker Detection — Automatically identifies participants 🔊 Audio Summaries — Listen to key points (MP3/WAV) 📝 Clickable Timestamps — Every quote links directly to that moment in the video 💬 YouTube Comments — Viewer sentiment analysis and best comments 📋 Queue Support — Send multiple links, they get processed in order 🚀 Non-Blocking Workflow — Conversation continues while video processes in background

🎬 Works With Any Video

Interviews & podcasts (multi-speaker detection) Lectures & tutorials (single speaker) Music videos (lyrics extraction) News & documentaries Any YouTube content with captions

Quick Start

When user sends a YouTube URL: Spawn sub-agent with the full pipeline task immediately Reply: "🎬 TubeScribe is processing — I'll let you know when it's ready!" Continue conversation (don't wait!) Sub-agent notification will announce completion with title and details DO NOT BLOCK — spawn and move on instantly.

First-Time Setup

Run setup to check dependencies and configure defaults: python skills/tubescribe/scripts/setup.py This checks: summarize CLI, pandoc, ffmpeg, Kokoro TTS

Full Workflow (Single Sub-Agent)

Spawn ONE sub-agent that does the entire pipeline: sessions_spawn( task=f""" ## TubeScribe: Process {youtube_url} ⚠️ CRITICAL: Do NOT install any software. No pip, brew, curl, venv, or binary downloads. If a tool is missing, STOP and report what's needed. Run the COMPLETE pipeline — do not stop until all steps are done. ### Step 1: Extract ```bash python3 skills/tubescribe/scripts/tubescribe.py "{youtube_url}" Note the Source and Output paths printed by the script. Use those exact paths in subsequent steps.

Step 2: Read source JSON

Read the Source path from Step 1 output and note: metadata.title (for filename) metadata.video_id metadata.channel, upload_date, duration_string

Step 3: Create formatted markdown

Write to the Output path from Step 1: # **<title>** Video info block — Channel, Date, Duration, URL (clickable). Empty line between each field. ## **Participants** — table with bold headers: | **Name** | **Role** | **Description** | |----------|----------|-----------------| ## **Summary** — 3-5 paragraphs of prose ## **Key Quotes** — 5 best with clickable YouTube timestamps. Format each as: "Quote text here." - [12:34](https://www.youtube.com/watch?v=ID&t=754s) "Another quote." - [25:10](https://www.youtube.com/watch?v=ID&t=1510s) Use regular dash -, NOT em dash —. Do NOT use blockquotes >. Plain paragraphs only. ## **Viewer Sentiment** (if comments exist) ## **Best Comments** (if comments exist) — Top 5, NO lines between them: Comment text here. *- ▲ 123 @AuthorName* Next comment text here. *- ▲ 45 @AnotherAuthor* Attribution line: dash + italic. Just blank line between comments, NO --- separators. ## **Full Transcript** — merge segments, speaker labels, clickable timestamps

Step 4: Create DOCX

Clean the title for filename (remove special chars), then: pandoc <output_path> -o ~/Documents/TubeScribe/<safe_title>.docx

Step 5: Generate audio

Write the summary text to a temp file, then use TubeScribe's built-in audio generation: # Write summary to temp file (use python3 to write, avoids shell escaping issues) python3 -c " text = '''YOUR SUMMARY TEXT HERE''' with open('<temp_dir>/tubescribe_<video_id>_summary.txt', 'w') as f: f.write(text) " # Generate audio (auto-detects engine, voice, format from config) python3 skills/tubescribe/scripts/tubescribe.py \ --generate-audio <temp_dir>/tubescribe_<video_id>_summary.txt \ --audio-output ~/Documents/TubeScribe/<safe_title>_summary This reads ~/.tubescribe/config.json and uses the configured TTS engine (mlx/kokoro/builtin), voice blend, and speed automatically. Output format (mp3/wav) comes from config.

Step 6: Cleanup

python3 skills/tubescribe/scripts/tubescribe.py --cleanup <video_id>

Step 7: Open folder

open ~/Documents/TubeScribe/

Report

Tell what was created: DOCX name, MP3 name + duration, video stats. """, label="tubescribe", runTimeoutSeconds=900, cleanup="delete" ) **After spawning, reply immediately:** > 🎬 TubeScribe is processing - I'll let you know when it's ready! Then continue the conversation. The sub-agent notification announces completion. ## Configuration Config file: `~/.tubescribe/config.json` ```json { "output": { "folder": "~/Documents/TubeScribe", "open_folder_after": true, "open_document_after": false, "open_audio_after": false }, "document": { "format": "docx", "engine": "pandoc" }, "audio": { "enabled": true, "format": "mp3", "tts_engine": "mlx" }, "mlx_audio": { "path": "~/.openclaw/tools/mlx-audio", "model": "mlx-community/Kokoro-82M-bf16", "voice": "af_heart", "lang_code": "a", "speed": 1.05 }, "kokoro": { "path": "~/.openclaw/tools/kokoro", "voice_blend": { "af_heart": 0.6, "af_sky": 0.4 }, "speed": 1.05 }, "processing": { "subagent_timeout": 600, "cleanup_temp_files": true } }

Output Options

OptionDefaultDescriptionoutput.folder~/Documents/TubeScribeWhere to save filesoutput.open_folder_aftertrueOpen output folder when doneoutput.open_document_afterfalseAuto-open generated documentoutput.open_audio_afterfalseAuto-open generated audio summary

Document Options

OptionDefaultValuesDescriptiondocument.formatdocxdocx, html, mdOutput formatdocument.enginepandocpandocConverter for DOCX (falls back to HTML)

Audio Options

OptionDefaultValuesDescriptionaudio.enabledtruetrue, falseGenerate audio summaryaudio.formatmp3mp3, wavAudio format (mp3 needs ffmpeg)audio.tts_enginemlxmlx, kokoro, builtinTTS engine (mlx = fastest on Apple Silicon)

MLX-Audio Options (preferred on Apple Silicon)

OptionDefaultDescriptionmlx_audio.path~/.openclaw/tools/mlx-audiomlx-audio venv locationmlx_audio.modelmlx-community/Kokoro-82M-bf16MLX model to usemlx_audio.voiceaf_heartVoice preset (used if no voice_blend)mlx_audio.voice_blend{af_heart: 0.6, af_sky: 0.4}Custom voice mix (weighted blend)mlx_audio.lang_codeaLanguage code (a=US English)mlx_audio.speed1.05Playback speed (1.0 = normal, 1.05 = 5% faster)

Kokoro PyTorch Options (fallback)

OptionDefaultDescriptionkokoro.path~/.openclaw/tools/kokoroKokoro repo locationkokoro.voice_blend{af_heart: 0.6, af_sky: 0.4}Custom voice mixkokoro.speed1.05Playback speed (1.0 = normal, 1.05 = 5% faster)

Processing Options

OptionDefaultDescriptionprocessing.subagent_timeout600Seconds for sub-agent (increase for long videos)processing.cleanup_temp_filestrueRemove /tmp files after completion

Comment Options

OptionDefaultDescriptioncomments.max_count50Number of comments to fetchcomments.timeout90Timeout for comment fetching (seconds)

Queue Options

OptionDefaultDescriptionqueue.stale_minutes30Consider a processing job stale after this many minutes

Output Structure

~/Documents/TubeScribe/ ├── {Video Title}.html # Formatted document (or .docx / .md) └── {Video Title}_summary.mp3 # Audio summary (or .wav) After generation, opens the folder (not individual files) so you can access everything.

Dependencies

Required: summarize CLI — brew install steipete/tap/summarize Python 3.8+ Optional (better quality): pandoc — DOCX output: brew install pandoc ffmpeg — MP3 audio: brew install ffmpeg yt-dlp — YouTube comments: brew install yt-dlp mlx-audio — Fastest TTS on Apple Silicon: pip install mlx-audio (uses MLX backend for Kokoro) Kokoro TTS — PyTorch fallback: see https://github.com/hexgrad/kokoro

yt-dlp Search Paths

TubeScribe checks these locations (in order): PriorityPathSource1which yt-dlpSystem PATH2/opt/homebrew/bin/yt-dlpHomebrew (Apple Silicon)3/usr/local/bin/yt-dlpHomebrew (Intel) / Linux4~/.local/bin/yt-dlppip install --user5~/.local/pipx/venvs/yt-dlp/bin/yt-dlppipx6~/.openclaw/tools/yt-dlp/yt-dlpTubeScribe auto-install If not found, setup downloads a standalone binary to the tools directory. The tools directory version doesn't conflict with system installations.

Queue Handling

When user sends multiple YouTube URLs while one is processing:

Check Before Starting

python skills/tubescribe/scripts/tubescribe.py --queue-status

If Already Processing

# Add to queue instead of starting parallel processing python skills/tubescribe/scripts/tubescribe.py --queue-add "NEW_URL" # → Replies: "📋 Added to queue (position 2)"

After Completion

# Check if more in queue python skills/tubescribe/scripts/tubescribe.py --queue-next # → Automatically pops and processes next URL

Queue Commands

CommandDescription--queue-statusShow what's processing + queued items--queue-add URLAdd URL to queue--queue-nextProcess next item from queue--queue-clearClear entire queue

Batch Processing (multiple URLs at once)

python skills/tubescribe/scripts/tubescribe.py url1 url2 url3 Processes all URLs sequentially with a summary at the end.

Error Handling

The script detects and reports these errors with clear messages: ErrorMessageInvalid URL❌ Not a valid YouTube URLPrivate video❌ Video is private — can't accessVideo removed❌ Video not found or removedNo captions❌ No captions available for this videoAge-restricted❌ Age-restricted video — can't access without loginRegion-blocked❌ Video blocked in your regionLive stream❌ Live streams not supported — wait until it endsNetwork error❌ Network error — check your connectionTimeout❌ Request timed out — try again later When an error occurs, report it to the user and don't proceed with that video.

Tips

For long videos (>30 min), increase sub-agent timeout to 900s Speaker detection works best with clear interview/podcast formats Single-speaker videos (tutorials, lectures) skip speaker labels automatically Timestamps link directly to YouTube at that moment Use batch mode for multiple videos: tubescribe url1 url2 url3

Category context

Code helpers, APIs, CLIs, browser automation, testing, and developer operations.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package

3 Docs3 Scripts

SKILL.md Primary doc
CHANGELOG.md Docs
README.md Docs
scripts/config.py Scripts
scripts/html_writer.py Scripts
scripts/setup.py Scripts