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	1.0.0
license	MIT
author	Jeremy Longshore <[e-mail]>

TwinMind Core Workflow A: Meeting Transcription & Summary

Overview

Primary workflow for capturing meetings, generating transcripts, and creating AI summaries.

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

// src/workflows/meeting-capture.ts
import { getTwinMindClient } from '../twinmind/client';
import { Transcript, Summary } from '../twinmind/types';

interface MeetingOptions {
  title?: string;
  calendarEventId?: string;
  language?: string;
  enableDiarization?: boolean;
}

export class MeetingCapture {
  private client = getTwinMindClient();

  async startLiveCapture(options: MeetingOptions = {}): Promise<string> {
    const response = await this.client.post('/meetings/live/start', {
      title: options.title || `Meeting ${new Date().toISOString()}`,
      calendar_event_id: options.calendarEventId,
      language: options.language || 'auto',
      diarization: options.enableDiarization ?? true,
      model: ,
    });

     response..;
  }

   (: ): <> {
     response =  ..();
     response..;
  }

   (: , :  = {}): <> {
     response =  ..(, {
      : audioUrl,
      : options.,
      : options. || ,
      : options. ?? ,
      : ,
    });

     .(response..);
  }

    (: , maxWaitMs = ): <> {
     startTime = .();
     pollIntervalMs = ;

     (.() - startTime < maxWaitMs) {
       response =  ..();

       (response.. === ) {
         response.;
      }

       (response.. === ) {
          ();
      }

        ( (r, pollIntervalMs));
    }

      ();
  }
}

Step 2: Generate AI Summary

// src/workflows/summary-generation.ts
export interface SummaryOptions {
  format?: 'brief' | 'detailed' | 'bullet-points';
  includeActionItems?: boolean;
  includeKeyPoints?: boolean;
  maxLength?: number;
}

export class SummaryGenerator {
  private client = getTwinMindClient();

  async generateSummary(
    transcriptId: string,
    options: SummaryOptions = {}
  ): Promise<Summary> {
    const response = await this.client.post('/summarize', {
      transcript_id: transcriptId,
      format: options.format || 'detailed',
      include_action_items: options.includeActionItems ?? true,
      include_key_points: options.includeKeyPoints ?? true,
      max_length: options.maxLength || 500,
    });

    return response.data;
  }

  async generateFollowUpEmail(: ): <> {
     response =  ..(, {
      : transcriptId,
    });

     response..;
  }

   (: ): <> {
     response =  ..(, {
      : transcriptId,
      : ,
    });

     response..;
  }
}

Step 3: Handle Speaker Identification

// src/workflows/speaker-handling.ts
export interface Speaker {
  id: string;
  name?: string;
  email?: string;
  speakingTime: number;
  segments: number;
}

export class SpeakerManager {
  async identifySpeakers(transcript: Transcript, attendees?: string[]): Promise<Speaker[]> {
    const speakers = new Map<string, Speaker>();

    for (const segment of transcript.segments) {
      const speakerId = segment.speaker_id || 'unknown';
      const existing = speakers.get(speakerId);

      if (existing) {
        existing.speakingTime += segment.end - segment.start;
        existing.segments += 1;
      } else {
        speakers.set(speakerId, {
          id: speakerId,
          speakingTime: segment.end - segment.,
          : ,
        });
      }
    }

    
     (attendees && attendees. > ) {
      
       matched =  .(
        .(speakers.()),
        attendees
      );
       matched;
    }

     .(speakers.());
  }

    (: [], : []): <[]> {
     client = ();
     response =  client.(, {
      : speakers.( s.),
      attendees,
    });

     speakers.( ({
      ...speaker,
      : response..[idx]?.,
      : response..[idx]?.,
    }));
  }
}

Step 4: Complete Workflow Orchestration

// src/workflows/full-meeting-workflow.ts
import { MeetingCapture } from './meeting-capture';
import { SummaryGenerator } from './summary-generation';
import { SpeakerManager } from './speaker-handling';

export interface MeetingResult {
  transcriptId: string;
  transcript: Transcript;
  summary: Summary;
  speakers: Speaker[];
  followUpEmail?: string;
  meetingNotes?: string;
}

export async function processMeeting(
  audioUrl: string,
  options: {
    title?: string;
    attendees?: string[];
    generateEmail?: boolean;
    generateNotes?: boolean;
  } = {}
): Promise<MeetingResult> {
  const capture = new MeetingCapture();
  const summaryGen = new SummaryGenerator();
  const speakerMgr = new SpeakerManager();

  
  .();
   transcript =  capture.(audioUrl, {
    : options.,
    : ,
  });
  .();

  
  .();
   [summary, speakers] =  .([
    summaryGen.(transcript., {
      : ,
      : ,
      : ,
    }),
    speakerMgr.(transcript, options.),
  ]);

   :  = {
    : transcript.,
    transcript,
    summary,
    speakers,
  };

  
   (options.) {
    result. =  summaryGen.(transcript.);
  }

   (options.) {
    result. =  summaryGen.(transcript.);
  }

   result;
}


  () {
   result =  (
    ,
    {
      : ,
      : [, ],
      : ,
      : ,
    }
  );

  .();
  .();
  .();
  .();
}

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

Example console output:

Starting transcription...
Transcription complete: tr_abc123
Generating summary and identifying speakers...
Meeting processed successfully!
Summary: Daily standup covering sprint progress and blockers...
Action Items: 3
Speakers: Alice, Bob, Charlie

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

Audio Format Support

Format	Extension	Supported	Notes
MP3	.mp3	Yes	Recommended
WAV	.wav	Yes	Best quality
M4A	.m4a	Yes	iOS recordings
WebM	.webm	Yes	Browser recordings
OGG	.ogg	Yes	Open format
FLAC	.flac	Yes	Lossless

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.