Twinmind Core Workflow A

---
name: twinmind-core-workflow-a
description: 'Execute TwinMind primary workflow: Meeting transcription and summary
  generation.

  Use when implementing meeting capture, building transcription features,

  or automating meeting documentation.

  Trigger with phrases like "twinmind transcription workflow",

  "meeting transcription", "capture meeting with twinmind".

  '
allowed-tools: Read, Write, Edit, Bash(npm:*), Grep
version: 1.13.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
tags:
- saas
- twinmind
- transcription
- workflow
compatibility: Designed for Claude Code
---
# TwinMind Core Workflow A: Meeting Transcription & Summary

## Contents

- [Overview](#overview)
- [Prerequisites](#prerequisites)
- [Instructions](#instructions)
- [Output](#output)
- [Error Handling](#error-handling)
- [Examples](#examples)
- [Resources](#resources)

## Overview

Primary workflow for capturing meetings, generating transcripts with speaker diarization, and creating AI summaries with action items.

## Prerequisites

- Completed `twinmind-install-auth` setup
- TwinMind Pro/Enterprise for API access
- Valid API credentials configured
- Audio source available (live or file)

## Instructions

### Step 1: Initialize Meeting Capture

Build a `MeetingCapture` class with `startLiveCapture()` for real-time recording and `transcribeRecording()` for file-based transcription. Use Ear-3 model with auto language detection and speaker diarization.

### Step 2: Generate AI Summary

Create a `SummaryGenerator` with `generateSummary()` (brief/detailed/bullet-points formats), `generateFollowUpEmail()`, and `generateMeetingNotes()` methods.

### Step 3: Handle Speaker Identification

Build a `SpeakerManager` that extracts speakers from transcript segments, calculates speaking time per speaker, and optionally matches speakers to calendar attendees.

### Step 4: Orchestrate Complete Workflow

Wire everything together in `processMeeting()`: transcribe audio, then generate summary and identify speakers in parallel, optionally produce follow-up email and meeting notes.

See detailed implementation for complete MeetingCapture, SummaryGenerator, SpeakerManager, and orchestration code.

## Output

- Complete meeting transcript with timestamps
- Speaker-labeled segments
- AI-generated summary
- Extracted action items with assignees
- Optional follow-up email draft
- Optional formatted meeting notes

## Error Handling

| Error | Cause | Solution |
|-------|-------|----------|
| Transcription timeout | Large audio file | Increase maxWaitMs or use async callback |
| Speaker match failed | No calendar data | Provide attendees list manually |
| Summary generation failed | Transcript too short | Ensure minimum 30s of audio |
| Audio format unsupported | Wrong codec | Convert to MP3/WAV/M4A |
| Rate limit exceeded | Too many requests | Implement queue-based processing |

## Examples

**Basic usage**: Apply twinmind core workflow a to a standard project setup with default configuration options.

**Advanced scenario**: Customize twinmind core workflow a for production environments with multiple constraints and team-specific requirements.

## Audio Format Support

| Format | Supported | Notes |
|--------|-----------|-------|
| MP3 | Yes | Recommended |
| WAV | Yes | Best quality |
| M4A | Yes | iOS recordings |
| WebM | Yes | Browser recordings |

## Resources

- TwinMind Transcription API
- Ear-3 Model Details
- Audio Format Guide

## Next Steps

For action item extraction and follow-up automation, see `twinmind-core-workflow-b`.