Loom Workflow

# Loom Workflow Analyzer

Transforms Loom recordings into structured, automatable workflows.

Quick Start

```bash # Full pipeline - download, extract, transcribe, analyze {baseDir}/scripts/loom-workflow analyze https://loom.com/share/abc123

# Individual steps {baseDir}/scripts/loom-workflow download https://loom.com/share/abc123 {baseDir}/scripts/loom-workflow extract ./video.mp4 {baseDir}/scripts/loom-workflow generate ./analysis.json ```

Pipeline

1. Download - Fetches Loom video via yt-dlp
2. Smart Extract - Captures frames at scene changes + transcript timing
3. Transcribe - Whisper transcription with word-level timestamps
4. Analyze - Multimodal AI analysis (requires vision model)
5. Generate - Creates Lobster workflow with approval gates

Smart Frame Extraction

• Frames are captured when:
• Scene changes - Significant visual change (ffmpeg scene detection)
• Speech starts - New narration segment begins
• Combined - Speech + visual change = high-value moment
• Gap fill - Max 10s without a frame

Analysis Output

• The analyzer produces:
• `workflow-analysis.json` - Structured workflow definition
• `workflow-summary.md` - Human-readable summary
• `*.lobster` - Executable Lobster workflow file

Ambiguity Detection

• The analyzer flags:
• Unclear mouse movements
• Implicit knowledge ("the usual process")
• Decision points ("depending on...")
• Missing credentials/context
• Tool dependencies

Vision Analysis Step

After extraction, use the generated prompt with a vision model:

```bash # The prompt is at: output/workflow-analysis-prompt.md # Attach frames from: output/frames/

# Example with Claude: cat output/workflow-analysis-prompt.md | claude --images output/frames/*.jpg ```

Save the JSON response to `workflow-analysis.json`, then:

```bash {baseDir}/scripts/loom-workflow generate ./output/workflow-analysis.json ```

Lobster Integration

• Generated workflows use:
• `approve` gates for destructive/external actions
• `llm-task` for classification/decision steps
• Resume tokens for interrupted workflows
• JSON piping between steps

Requirements

• `yt-dlp` - Video download
• `ffmpeg` - Frame extraction + scene detection
• `whisper` - Audio transcription
• Vision-capable LLM for analysis step

Multilingual Support

Works with any language - Whisper auto-detects and transcribes. Analysis should be prompted in the video's language for best results.