openrouter-compliance-review
Review OpenRouter integration for regulatory compliance (SOC2, GDPR,
twinmind-hello-world
Create your first TwinMind meeting transcription and AI summary.
Full skill instructions
Create your first meeting transcription with AI-generated summary and action items.
twinmind-install-auth setupOption A - Browser Meeting:
Option B - Voice Memo:
For a meaningful test, speak for 30-60 seconds covering:
"Welcome to today's project status meeting.
We have three items on the agenda.
First, the mobile app launch is scheduled for next Friday.
Sarah will handle the App Store submission.
Second, we need to review the Q1 budget.
John, please send the spreadsheet by Wednesday.
Third, the customer feedback survey shows 85% satisfaction.
We should schedule a follow-up meeting next week to discuss improvements."
Expected transcript output:
[00:00] Welcome to today's project status meeting...
[00:05] We have three items on the agenda...
[00:12] First, the mobile app launch is scheduled for next Friday...
[00:18] Sarah will handle the App Store submission...
Expected AI summary:
## Meeting Summary
Project status meeting covering mobile app launch, Q1 budget review,
and customer feedback analysis.
## Action Items
- [ ] Sarah: Submit app to App Store (Due: Friday)
- [ ] John: Send Q1 budget spreadsheet (Due: Wednesday)
- [ ] Team: Schedule follow-up meeting for feedback discussion
## Key Points
- Mobile app launching next Friday
- Customer satisfaction at 85%
- Budget review pending
After the meeting:
// TwinMind stores transcripts in your Memory Vault
// Access via extension sidebar or ask AI:
"What did we discuss about the mobile app launch?"
"Who is responsible for the budget spreadsheet?"
"When is the next meeting scheduled?"
Transcription complete!
Duration: 1m 23s
Words: 156
Speakers: 1
Language: English
AI Summary: Generated
Action Items: 3 extracted
| Error | Cause | Solution |
|---|---|---|
| No audio detected | Microphone not selected | Check audio input settings |
| Transcript empty | Audio too quiet | Increase microphone volume |
| Summary not generated | Processing timeout | Retry or check network |
| Speaker labels wrong | Single speaker test | Use multi-speaker content |
| Sync failed | Network interruption | Check connection, retry |
// TwinMind uses Ear-3 model with:
// - 5.26% Word Error Rate (industry-leading)
// - 3.8% Diarization Error Rate
// - 140+ language support
// Quality indicators in UI:
// - Green: High confidence (>95%)
// - Yellow: Medium confidence (80-95%)
// - Red: Low confidence (<80%)
TwinMind routes queries to optimal models:
// Perfect for capturing ideas on the go
// 1. Click extension
// 2. Voice memo mode
// 3. Speak thought
// 4. Auto-transcribed and indexed
"Note to self: Follow up with the design team about
the new color palette before Thursday's review."
// Result: Indexed, searchable, reminded via calendar
// TwinMind automatically labels speakers
// Speaker diarization identifies who said what
// Output format:
// [Speaker 1 - 00:00]: "Let's start the standup..."
// [Speaker 2 - 00:15]: "I completed the API integration..."
// [Speaker 1 - 00:32]: "Great work. Any blockers?"
Proceed to twinmind-local-dev-loop for development workflow integration.
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