Loom Workflow OpenClaw Skill - ClawHub
Do you want your AI agent to automate Loom Workflow workflows? This free skill from ClawHub helps with browser & automation tasks without building custom tools from scratch.
What this skill does
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
Install
npx clawhub@latest install loom-workflowFull SKILL.md
Open original| name | description |
|---|---|
| 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 |
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
- Download - Fetches Loom video via yt-dlp
- Smart Extract - Captures frames at scene changes + transcript timing
- Transcribe - Whisper transcription with word-level timestamps
- Analyze - Multimodal AI analysis (requires vision model)
- 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 definitionworkflow-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:
approvegates for destructive/external actionsllm-taskfor classification/decision steps- Resume tokens for interrupted workflows
- JSON piping between steps
Requirements
yt-dlp- Video downloadffmpeg- Frame extraction + scene detectionwhisper- 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.