email-triage

Automated email triage analyzes message content, sender profile memory, and thread context to classify incoming emails into categories like URGENT, REPLY_NEEDED, or FYI. This reduces manual sorting time and accelerates response prioritization for high-volume inboxes.

Thread detection for email triage differentiates new messages from ongoing conversations by analyzing content and sender context. This helps route helpdesk tickets accurately and maintains conversation continuity without losing historical message context.

Memory recall improves automated email classification by storing and updating sender profiles over time. The triage system uses this historical sender data to increase confidence scores and make more accurate categorization decisions for future incoming messages.

Content-based email routing uses NLP analysis of subject lines and body text to assign triage categories with confidence scores. Messages are then automatically directed to appropriate teams or action queues based on their classified priority level.

The email triage skill operates with zero external dependencies, requiring no additional components or API connections. It performs classification, thread detection, and sender memory updates entirely through its internal rule-based processing logic.

Summarizing inbox workload involves applying automated triage classification across all messages to categorize them by type and urgency. This provides a clear overview of required actions and helps prioritize urgent items in high-volume mailboxes.