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chunk-process

Skill by Nuva-Lab

IndexedApache-2.0★ 6
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Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/nuva-lab-chunk-process

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What's inside

Skill name
chunk-process
Description
None
License
Apache-2.0
Instructions
84 lines in SKILL.md · view on GitHub

Before installing

  • Ships executable scripts

Agent Skills spec issues

  • missing YAML frontmatter
  • name: missing
  • description: missing

Files (5)

  • SKILL.md
  • batch_transcribe.py
  • mlx_transcribe.py
  • process_chunks.py
  • smart_chunk.py

SKILL.md (first lines)

# Chunk Process Skill

Smart video chunking and MLX-accelerated transcription for long-form content.

## Problem Solved
- Raw footage too long for single Gemini upload (~47 min = 5GB+)
- Need word-level timestamps for precise cutting
- Fixed-length chunks break mid-sentence

## Smart Chunking

Instead of fixed 5-minute segments, `smart_chunk.py` finds natural break points:

```bash
python skills/chunk-process/smart_chunk.py raw_footage.mp4 -o chunks/
```

**How it works:**
1. Detect silence regions (>500ms gaps)
2. Target 2.5-3.5 minute chunks
3. Split at natural pauses, not mid-sentence
4. Output: `chunk_001.mp4`, `chunk_002.mp4`, ...

**Options:**
- `--min-chunk 150`: Minimum chunk length (seconds)
- `--max-chunk 210`: Maximum chunk length (seconds)
- `--silence-thresh -40`: Silence detection threshold (dB)

## MLX Transcription

`mlx_transcribe.py` uses MLX-accelerated Qwen3-ASR for fast transcription on Mac:

```bash
# Single file
python skills/chunk-process/mlx_transcribe.py audio.wav -o transcript.json

# Batch process chunks
python skills/chunk-process/mlx_transcribe.py chunks/ --batch --word-timestamps
```

**Features:**
- 3-5x faster than CPU on Apple Silicon
- Auto language detection (Chinese/English/Mixed)
- Word-level timestamps (~30ms precision)
- Outputs: `transcript.json` with segments + words

## Combined Pipeline

```bash
# 1. Smart chunk the video
python skills/chunk-process/smart_chunk.py raw.mp4 -o chunks/

# 2. Transcribe all chunks
python skills/chunk-process/mlx_transcribe.py chunks/ --batch --word-timestamps

# Output: chunks/transcript.json (merged from all chunks)
```

## Output Format

```json
{
  "language": "English",
  "segments": [
    {"text": "First sentence.", "start": 0.0, "end": 2.5},
    {"text": "Second sentence.", "start": 2.5, "end": 5.0}
  ],
  "words": [
    {"text": "First", "start": 0.0, "end": 0.3},
    {"text": "sentence", "start": 0.3, "end": 0.8}
  ],
  "full_text": "First sentence. Second sentence..."
}
```

## Why Smart Chunking?

| Fixed Chunks | Smart Chunks |
|--------------|--------------|
| Breaks mid-word | Breaks at pauses |
| 5 min arbitrary | 2.5-3.5 min natural |
| Hard cuts | Clean transitions |
| Timestamp gaps | Continuous timeline |

From Nuva-Lab/vibecut, Apache-2.0.

More from Nuva-Lab/vibecut

Signals

Stars
6
Forks
1
Open issues
0
Last commit (this folder)
Jan 31, 2026 (9 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from Nuva-Lab

Cite this page

chunk-process skill. Agent Mart. https://agentmart.dev/skills/nuva-lab-chunk-process (last updated 2026-10-24)