tubescribe

name	TubeScribe
description	YouTube video summarizer with speaker detection, formatted documents, and audio output. Use when user sends a YouTube URL or asks to summarize/transcribe a YouTube video.

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.

💸 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

✨ 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:

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, 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 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>**

---

2. Video info block — Channel, Date, Duration, URL (clickable). Empty line between each field.

---

3. ## **Participants** — table with bold headers:

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

---

4. ## **Summary** — 3-5 paragraphs of prose

---

5. ## **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.

---

6. ## **Viewer Sentiment** (if comments exist)

---

7. ## **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.

---

8. ## **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

Read ~/.tubescribe/config.json to check audio.tts_engine and kokoro.path.

• If tts_engine is "kokoro": activate Kokoro from the configured path, generate with voice blend from config, save as MP3 to the configured output folder.
• If tts_engine is "builtin": use say command (macOS) to generate audio.
• If audio.enabled is false: skip this step.

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": "builtin"
  },
  "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	builtin	builtin, kokoro	TTS engine (builtin = macOS say)

Kokoro TTS Options (optional)

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
• Kokoro TTS — High-quality voices: 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