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    loom-workflow

    AI-native workflow analyzer for Loom recordings.

    By @g9pedro
    View on GitHub
    SKILL.md
    ---
    name: loom-workflow
    description: |
      AI-native workflow analyzer for Loom recordings. Breaks down recorded business processes
      into structured, automatable workflows. Use when:
      - Analyzing Loom videos to understand workflows
      - Extracting steps, tools, and decision points from screen recordings
      - Generating Lobster workflow files from video walkthroughs
      - Identifying ambiguities and human intervention points in processes
    ---
    
    # 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.