email-triage

Name: email-triage
Availability: InStock
Author: vladkesler

Classify emails into triage categories using content, sender memory, and thread context.

39|6|Updated Feb 9, 2026

Search Tags:#automation #email #memory #nlp #classification #triage #thread-detection

Ready to run

npx skills add https://github.com/vladkesler/initrunner --skill email-triage-vladkesler

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: email-triage
Source: https://github.com/vladkesler/initrunner/tree/main/examples/roles/email-agent/skills/email-triage
Command: npx skills add https://github.com/vladkesler/initrunner --skill email-triage-vladkesler

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Manual triage of incoming emails is time-consuming and error-prone. This skill automatically analyzes content, sender memory, and thread context to categorize messages into URGENT, REPLY_NEEDED, FYI, NEWSLETTER, NOTIFICATION, or SPAM, reducing response times and improving prioritization.

Core Features & Use Cases

Automated email classification using subject, body, and sender profile memory to assign categories with confidence scores.
Memory recall and update of sender profiles to improve future triage decisions.
Thread detection to differentiate new messages from ongoing conversations.
Use cases include routing to appropriate teams, summarizing inbox workloads, and prioritizing urgent items in high-volume mailboxes.

Quick Start

Classify this email payload into a triage category based on content and sender context.

Frequently Asked Questions about email-triage

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I automatically classify and prioritize incoming emails by urgency?▼

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.

How does thread detection work for email triage in helpdesk queues?▼

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.

Can I use memory recall to improve automated email classification accuracy?▼

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.

What's the best way to route emails to appropriate teams based on content analysis?▼

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.

Does email triage work without external dependencies or API connections?▼

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.

How do I summarize inbox workload for high-volume mailboxes?▼

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.