# Jeremylongshore Claude Code Plugins Plus Skills Twinmind Core Workflow A

> TwinMind Core Workflow A: Meeting Transcription & Summary

- Skill: `tomevault-io/jeremylongshore-claude-code-plugins-plus-skills-twinmind-cor` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add tomevault-io/jeremylongshore-claude-code-plugins-plus-skills-twinmind-cor`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/jeremylongshore-claude-code-plugins-plus-skills-twinmind-cor/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Productivity
- Author: tomevault-io (https://skillmd.com/u/tomevault-io)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tomevault-io/jeremylongshore-claude-code-plugins-plus-skills-twinmind-cor

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# 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](${CLAUDE_SKILL_DIR}/references/implementation.md) 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](https://twinmind.com/docs/transcription)
- [Ear-3 Model Details](https://twinmind.com/ear-3)
- [Audio Format Guide](https://twinmind.com/docs/audio-formats)

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

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