TubeScribe 🎬

Turn any YouTube video into a polished document + audio summary in seconds.

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.

💸 100% Free & Local

• •No subscription — runs entirely on your machine
• •No API keys required — works out of the box
• •No data leaves your computer — your content stays private
• •No usage limits — summarize as many videos as you want

✨ Features

• •🎯 Smart Speaker Detection — Automatically identifies who's talking in interviews, podcasts, and conversations
• •📝 Clickable Timestamps — Every quote links directly to that moment in the video
• •💬 YouTube Comments — Fetches top comments, summarizes viewer sentiment, highlights best reactions
• •📄 Clean Documents — Export as HTML, DOCX, or Markdown
• •🔊 Audio Summaries — Listen to the key points (MP3/WAV)

🎬 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:

1. •Spawn sub-agent with the full pipeline task immediately
2. •Reply: "🎬 TubeScribe is processing — I'll let you know when it's ready!"
3. •Continue conversation (don't wait!)
4. •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/python-docx, 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}

Run the COMPLETE pipeline — do not stop until all steps are done.

### Step 1: Extract
```bash
python3 /Users/matusvojtek/.openclaw/workspace/skills/tubescribe/scripts/tubescribe.py "{youtube_url}"

Note the video_id from the output (e.g., "Source: /tmp/tubescribe_ABC123_source.json" → video_id is ABC123).

Step 2: Read source JSON

Read /tmp/tubescribe_<video_id>_source.json and note:

• •metadata.title (for filename)
• •metadata.video_id
• •metadata.channel, upload_date, duration_string

Step 3: Create formatted markdown

Write to /tmp/tubescribe_<video_id>_output.md:

1. •# **<title>**

1. •Video info block (Channel, Date, Duration, clickable URL)

1. •## **Participants** — table with bold headers:
   code

   | **Name** | **Role** | **Description** |
   |----------|----------|-----------------|
   

1. •## **Summary** — 3-5 paragraphs

1. •## **Key Quotes** — 5 best with clickable YouTube timestamps

1. •## **Viewer Sentiment** (if comments exist)

1. •## **Best Comments** (if comments exist) — Top 5, NO lines between them:
   code

   Comment text here.
   
   <p align="right">▲ 123 @AuthorName</p>
   
   Next comment text here.
   
   <p align="right">▲ 45 @AnotherAuthor</p>
   

   Just blank line between comments, NO --- separators.

1. •## **Full Transcript** — merge segments, speaker labels, clickable timestamps

Step 4: Create DOCX

Clean the title for filename (remove special chars), then:

pandoc /tmp/tubescribe_<video_id>_output.md -o ~/Documents/TubeScribe/<safe_title>.docx

Step 5: Generate audio

cd ~/.openclaw/tools/kokoro && source .venv/bin/activate

Then Python: read Summary from markdown, generate with Kokoro (voice=0.6af_heart+0.4af_sky), save as MP3 to ~/Documents/TubeScribe/<safe_title>_summary.mp3

Step 6: Cleanup

python3 /Users/matusvojtek/.openclaw/workspace/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:**
> 🎬 Processing "[video title if known, or just the URL]" — 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": "builtin"
  },
  "kokoro": {
    "venv_path": "~/.tubescribe/kokoro-env",
    "voice_blend": { "af_heart": 0.6, "af_sky": 0.4 },
    "speed": 1.05
  },
  "processing": {
    "subagent_timeout": 600,
    "cleanup_temp_files": true
  }
}

Output Options

Document Options

Audio Options

Kokoro TTS Options (optional)

Processing Options

Comment Options

Queue Options

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
• •Kokoro TTS — High-quality voices: see https://github.com/hexgrad/kokoro

yt-dlp Search Paths

TubeScribe checks these locations (in order):

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

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:

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