Feedback: integrations-make

Documentation Feedback

Original URL: https://www.assemblyai.com/docs/integrations/make
Category: integrations
Generated: 05/08/2025, 4:27:55 pm

Claude Sonnet 4 Feedback

Generated: 05/08/2025, 4:27:54 pm

Technical Documentation Analysis: AssemblyAI Make Integration

Overall Assessment

This documentation provides a basic overview of the AssemblyAI Make integration but lacks depth and clarity needed for effective implementation. Here’s my detailed feedback:

🔴 Critical Issues

1. Missing Prerequisites Section

Problem: Users don’t know what they need before starting. Solution: Add a prerequisites section including:

## Prerequisites
- Active Make account (link to signup)
- AssemblyAI account with API key
- Basic familiarity with Make scenarios
- Audio files in supported formats (list formats and size limits)

2. Incomplete Module Documentation

Problem: Module descriptions are too brief and lack essential details. Solution: For each module, include:

Purpose: What it does and when to use it
Required fields: Mark mandatory vs optional parameters
Input/Output examples: Show actual data structures
Error handling: Common errors and solutions

🟡 Structure & Clarity Issues

3. Improve Quickstart Flow

Current: Generic steps without context Recommended:

## Complete Example: Transcribe Audio from Google Drive

This example shows how to:
1. Get audio file from Google Drive
2. Upload to AssemblyAI
3. Transcribe with sentiment analysis
4. Send results to Slack

### Step 1: Set up the trigger
[Detailed instructions with screenshots]

### Step 2: Configure AssemblyAI modules
[Specific field configurations]

### Step 3: Connect output to Slack
[Integration details]

4. Add Configuration Details

Missing information:

Supported audio formats and file size limits
Available Audio Intelligence models and their purposes
Webhook setup instructions for notifications
Rate limiting and quota information

🟢 Content Enhancements

5. Expand Examples Section

Add these practical examples:

## Common Use Cases

### Podcast Transcription Workflow
- Trigger: New file in Dropbox
- Process: Upload → Transcribe with speaker labels
- Output: Save transcript to Google Sheets

### Customer Call Analysis
- Trigger: New recording in cloud storage
- Process: Transcribe → Analyze sentiment → Extract PII
- Output: Create support ticket with insights

### Meeting Minutes Generator
- Trigger: Zoom recording webhook
- Process: Transcribe → Generate summary with LeMUR
- Output: Send formatted minutes via email

6. Improve Error Handling Documentation

## Troubleshooting

### Common Issues

#### Authentication Errors
- **Error**: "Invalid API key"
- **Solution**: Verify key from dashboard, check for extra spaces
- **Prevention**: Use connection test feature

#### File Upload Failures
- **Error**: "File too large"
- **Solution**: Files must be under 2GB
- **Workaround**: Use file compression or chunking

#### Transcript Processing Delays
- **Issue**: Long processing times
- **Explanation**: Processing time varies by file length
- **Monitoring**: Use webhook notifications for large files

🔧 Technical Improvements

7. Add Field Reference Tables

### Transcribe Audio File - Field Reference

| Field | Type | Required | Description | Example |
|-------|------|----------|-------------|---------|
| Audio URL | String | Yes | Publicly accessible audio file URL | `https://example.com/audio.mp3` |
| Speaker Labels | Boolean | No | Enable speaker identification | `true` |
| Sentiment Analysis | Boolean | No | Analyze emotional tone | `false` |
| Language Code | String | No | Audio language (auto-detect if empty) | `en` |

8. Improve Integration Flow Diagram

Add a visual workflow showing:

Data flow between modules
Decision points
Error handling paths
Output options

🎯 User Experience Improvements

9. Add Quick Reference Section

## Quick Reference

### Most Used Modules
1. **Upload a File** → **Transcribe Audio** (Basic transcription)
2. **Transcribe Audio** → **Get Sentences** (Detailed output)
3. **Transcribe Audio** → **LeMUR Task** (AI analysis)

### Processing Times
- Short audio (<5 min): 30-60 seconds
- Medium audio (5-30 min): 2-5 minutes
- Long audio (>30 min): 5-15 minutes

### Best Practices
- Use webhooks for files >10 minutes
- Enable only needed AI features to reduce processing time
- Store transcript IDs for future reference

10. Expand LeMUR Documentation

Current: Minimal explanation Needed:

What LeMUR does in plain language
Prompt examples for different use cases
Input text vs transcript ID usage
Token limits and pricing implications

🔄 Additional Recommendations

11. Add Version/Update Information

When was this integration last updated?
What Make plan is required?
Any known limitations or beta features?

Add a table of contents
Create anchor links for each module
Add “back to top” links in long sections

13. Include Migration Guide

For users upgrading from older versions or switching from other tools.

Summary Priority Actions

Immediate (High Impact): Add prerequisites, complete module documentation, add troubleshooting
Short-term (Medium Impact): Create detailed examples, add field references, improve structure
Long-term (Enhancement): Add visual diagrams, expand use cases, create video tutorials

This documentation has good bones but needs significant expansion to truly serve users effectively. Focus on the high-impact changes first to dramatically improve user success rates.