loom-workflow

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

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Install skill "loom-workflow" with this command: npx skills add G9Pedro/loom-workflow

Loom Workflow Analyzer

Transforms Loom recordings into structured, automatable workflows.

Quick Start

# 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:

# 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:

{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.

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