OpenClaw

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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查看来源 ↗安装与使用 SKILL.md ↗

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求，再添加到工作流。

SkillHub CLI

skillhub install g9pedro/loom-workflow

打开来源仓库，查看说明和兼容环境后，按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent，让它先读取说明、核对依赖，并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

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 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...

来源信息

Source: github
Repository: openclaw/skills
Path: skills/g9pedro/loom-workflow
Version: —
Commit: 41cbc8f30097a7eb750cc7d198d438e90be8e246
分类来源: rules
状态: active
可见性: public

这些信息来自收录时的来源分析，可能滞后；使用前请核对最新来源文件。

来源内容

SKILL.md

# 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...

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