alekseiul/tubescribe

metadata: { "claudeclaw": { "emoji": "🎬", "requires": { "bins": ["summarize"] } } }

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:

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 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:

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 <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": "~/.claudeclaw/tools/mlx-audio",
    "model": "mlx-community/Kokoro-82M-bf16",
    "voice": "af_heart",
    "lang_code": "a",
    "speed": 1.05
  },
  "kokoro": {
    "path": "~/.claudeclaw/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 | ~/.claudeclaw/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 | ~/.claudeclaw/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 | ~/.claudeclaw/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