Source Code

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

Option	Default	Description
`output.folder`	`~/Documents/TubeScribe`	Where to save files
`output.open_folder_after`	`true`	Open output folder when done
`output.open_document_after`	`false`	Auto-open generated document
`output.open_audio_after`	`false`	Auto-open generated audio summary

Document Options

Option	Default	Values	Description
`document.format`	`docx`	`docx`, `html`, `md`	Output format
`document.engine`	`pandoc`	`pandoc`	Converter for DOCX (falls back to HTML)

Audio Options

Option	Default	Values	Description
`audio.enabled`	`true`	`true`, `false`	Generate audio summary
`audio.format`	`mp3`	`mp3`, `wav`	Audio format (mp3 needs ffmpeg)
`audio.tts_engine`	`mlx`	`mlx`, `kokoro`, `builtin`	TTS engine (mlx = fastest on Apple Silicon)

MLX-Audio Options (preferred on Apple Silicon)

Option	Default	Description
`mlx_audio.path`	`~/.openclaw/tools/mlx-audio`	mlx-audio venv location
`mlx_audio.model`	`mlx-community/Kokoro-82M-bf16`	MLX model to use
`mlx_audio.voice`	`af_heart`	Voice 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_code`	`a`	Language code (a=US English)
`mlx_audio.speed`	`1.05`	Playback speed (1.0 = normal, 1.05 = 5% faster)

Kokoro PyTorch Options (fallback)

Option	Default	Description
`kokoro.path`	`~/.openclaw/tools/kokoro`	Kokoro repo location
`kokoro.voice_blend`	`{af_heart: 0.6, af_sky: 0.4}`	Custom voice mix
`kokoro.speed`	`1.05`	Playback speed (1.0 = normal, 1.05 = 5% faster)

Processing Options

Option	Default	Description
`processing.subagent_timeout`	`600`	Seconds for sub-agent (increase for long videos)
`processing.cleanup_temp_files`	`true`	Remove /tmp files after completion

Comment Options

Option	Default	Description
`comments.max_count`	`50`	Number of comments to fetch
`comments.timeout`	`90`	Timeout for comment fetching (seconds)

Queue Options

Option	Default	Description
`queue.stale_minutes`	`30`	Consider 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):

Priority	Path	Source
1	`which yt-dlp`	System PATH
2	`/opt/homebrew/bin/yt-dlp`	Homebrew (Apple Silicon)
3	`/usr/local/bin/yt-dlp`	Homebrew (Intel) / Linux
4	`~/.local/bin/yt-dlp`	pip install --user
5	`~/.local/pipx/venvs/yt-dlp/bin/yt-dlp`	pipx
6	`~/.openclaw/tools/yt-dlp/yt-dlp`	TubeScribe 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

Command	Description
`--queue-status`	Show what's processing + queued items
`--queue-add URL`	Add URL to queue
`--queue-next`	Process next item from queue
`--queue-clear`	Clear 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:

Error	Message
Invalid URL	❌ Not a valid YouTube URL
Private video	❌ Video is private — can't access
Video removed	❌ Video not found or removed
No captions	❌ No captions available for this video
Age-restricted	❌ Age-restricted video — can't access without login
Region-blocked	❌ Video blocked in your region
Live stream	❌ Live streams not supported — wait until it ends
Network error	❌ Network error — check your connection
Timeout	❌ 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