Developer quickstart
Minimal handler (mentions only)
Checklist
- Respect user notification preferences and quiet hours when sending alerts.
- Enrich notifications with context (linked entity, comment excerpt) for UX.
- De-duplicate multiple mentions in the same comment before notifying.
Event types
user:mentioned
Triggered when a user is mentioned in a comment across any entity type (tickets, account tasks, activities, or notes).
Payload structure:
Event structure
User events follow the standard platform event structure:Mention context
Entity types
Users can be mentioned in comments on different entity types:Ticket mentions
- Entity type:
TICKET
- Additional context:
teamId
is included in metadata - Common use cases: Agent collaboration, customer escalation, knowledge sharing
Account task mentions
- Entity type:
ACCOUNT_TASK
- Context: Task collaboration and assignment discussions
- Common use cases: Task handoffs, status updates, collaboration requests
Account activity mentions
- Entity type:
ACCOUNT_ACTIVITY
- Context: Activity discussions and follow-ups
- Common use cases: Activity reviews, next steps planning
Account note mentions
- Entity type:
ACCOUNT_NOTE
- Context: Note discussions and clarifications
- Common use cases: Knowledge sharing, note reviews, clarifications
Event processing
Mention detection
The system automatically detects mentions in comment content using patterns like:@username
@user.email
@"Full Name"
Deduplication
Multiple users can be mentioned in a single comment, generating separate events for each mentioned user.Self-mention filtering
Users mentioning themselves may be filtered out based on theignoreSelf
flag in the comment metadata.
Integration examples
Real-time notification system
Mention analytics
Smart notification routing
Mention context enhancement
User preference management
Mention patterns and best practices
Mention syntax support
The platform supports various mention formats:Integration best practices
- Deduplication: Handle duplicate mentions gracefully
- Rate limiting: Implement rate limiting for mention notifications
- Context preservation: Maintain mention context for better user experience
- Privacy: Respect user privacy settings and availability status
- Fallback handling: Handle cases where mentioned users don’t exist
Performance considerations
Error handling
Common error scenarios
Event frequency and scaling
Frequency characteristics
User mention events can vary greatly in frequency:- Low-volume organizations: Few mentions per day
- High-collaboration teams: Hundreds of mentions per hour
- Customer support teams: Spike during business hours
Scaling considerations
- Batch processing: Group mentions for efficient processing
- Async processing: Handle mention notifications asynchronously
- Caching: Cache user data and preferences for better performance
- Rate limiting: Prevent notification spam
- Monitoring: Track mention processing latency and success rates
Future enhancements
Potential future enhancements to user events:- Smart mentions: AI-suggested mentions based on context
- Group mentions: Mention entire teams or roles
- Mention threads: Track mention conversation threads
- Mention analytics: Advanced analytics for collaboration patterns
- Custom mention actions: Configurable actions when mentioned