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email-triage-responder

Analyze inbox emails to identify action-required items, prioritize by urgency/importance, classify by topic, and draft contextual replies. Use when triaging unread emails, prioritizing inbox, generating response drafts, or tracking email response status.

The English summary is being prepared. Showing the original description.

Works withGmailOutlook

Run score Not tested

See how to install

Files included (6)

  • SKILL.md5.9 KB
  • references/email-classification.md6.0 KB
  • references/response-templates.md7.2 KB
  • scripts/tests/conftest.py232 B
  • scripts/tests/test_triage_emails.py14.7 KB
  • scripts/triage_emails.py22.9 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Email Triage Responder

Overview

Analyze inbox emails to identify action-required items, prioritize them by urgency and importance using a 4-quadrant matrix, classify by topic (vendor inquiry, internal request, client follow-up), and generate contextual draft responses in appropriate tone and language. Integrates with Gmail/Outlook via gogcli or MCP tools to surface unread emails requiring attention.

When to Use

  • Triaging a large inbox with many unread emails
  • Prioritizing which emails need immediate attention
  • Classifying emails by topic or sender type
  • Generating draft responses for common email types
  • Tracking response status across multiple emails
  • Processing emails in bulk with consistent prioritization

Prerequisites

  • Python 3.9+
  • gogcli configured with Gmail OAuth (for Gmail integration)
  • Or Outlook MCP server configured (for Outlook integration)
  • No additional API keys required beyond email access

Workflow

Step 1: Fetch Unread Emails

Use gogcli or MCP tools to retrieve unread emails from the inbox.

# Gmail via gogcli
gogcli gmail messages list --query "is:unread" --format json --max-results 50

# Or use MCP server for Outlook
# (MCP tool invocation handled by Claude)

Step 2: Parse and Analyze Emails

Run the triage script to classify and prioritize emails.

python3 scripts/triage_emails.py \
  --input emails.json \
  --output triage_report.json

The script performs:

  1. Urgency Detection: Identifies time-sensitive language, deadlines, escalation markers
  2. Importance Classification: Evaluates sender (VIP, manager, client), CC/BCC patterns
  3. Topic Classification: Categorizes as vendor inquiry, internal request, client follow-up, FYI, etc.
  4. Action Detection: Determines if response, review, or delegation is needed

Step 3: Generate Priority Matrix

Categorize emails into 4 quadrants:

QuadrantUrgencyImportanceAction
Q1HighHighRespond immediately
Q2LowHighSchedule focused time
Q3HighLowDelegate or quick reply
Q4LowLowBatch process or archive

Step 4: Draft Contextual Responses

For each action-required email, generate a draft response:

python3 scripts/triage_emails.py \
  --input emails.json \
  --output drafts.json \
  --generate-drafts \
  --tone professional \
  --language auto

Draft generation considers:

  • Tone: Professional, friendly, formal (matches sender's tone)
  • Language: Auto-detect from original email (EN, JA, etc.)
  • Context: Previous thread history, sender relationship
  • Action Type: Acknowledgment, answer, request for info, delegation

Step 5: Track Response Status

Maintain a tracking file for email response status:

python3 scripts/triage_emails.py \
  --input emails.json \
  --status-file email_status.json \
  --update-status

Status tracking fields:

  • email_id: Unique identifier
  • status: pending, draft_ready, sent, delegated, archived
  • assigned_to: Owner if delegated
  • due_date: Expected response deadline
  • last_updated: Timestamp of last status change

Step 6: Generate Summary Report

Create a triage summary for review:

python3 scripts/triage_emails.py \
  --input emails.json \
  --output triage_report.md \
  --format markdown

Output Format

JSON Report

{
  "schema_version": "1.0",
  "generated_at": "2024-01-15T09:30:00Z",
  "summary": {
    "total_emails": 25,
    "action_required": 12,
    "by_quadrant": {
      "Q1_urgent_important": 3,
      "Q2_important_not_urgent": 5,
      "Q3_urgent_not_important": 2,
      "Q4_neither": 15
    },
    "by_topic": {
      "client_followup": 4,
      "internal_request": 6,
      "vendor_inquiry": 3,
      "fyi_informational": 8,
      "meeting_scheduling": 4
    }
  },
  "emails": [
    {
      "id": "msg_12345",
      "from": "client@example.com",
      "subject": "Urgent: Contract Review Needed",
      "received_at": "2024-01-15T08:00:00Z",
      "quadrant": "Q1",
      "urgency_score": 0.9,
      "importance_score": 0.85,
      "topic": "client_followup",
      "action_required": "respond",
      "detected_deadline": "2024-01-16T17:00:00Z",
      "draft_response": "Thank you for sending the contract...",
      "status": "draft_ready"
    }
  ]
}

Markdown Report

# Email Triage Report

**Generated**: 2024-01-15 09:30 AM
**Total Emails**: 25 | **Action Required**: 12

## Priority Matrix

### Q1: Urgent & Important (3 emails)
| From | Subject | Deadline | Status |
|------|---------|----------|--------|
| client@example.com | Urgent: Contract Review | Jan 16 | Draft Ready |

### Q2: Important, Not Urgent (5 emails)
...

## Topic Breakdown

- Client Follow-ups: 4
- Internal Requests: 6
- Vendor Inquiries: 3

## Recommended Actions

1. **Respond immediately** to 3 Q1 emails
2. **Schedule 30 min** for 5 Q2 emails
3. **Delegate** 2 Q3 emails to team

Resources

  • scripts/triage_emails.py -- Main triage and draft generation script
  • references/email-classification.md -- Topic taxonomy and urgency markers
  • references/response-templates.md -- Draft response templates by category

Key Principles

  1. Eisenhower Matrix: Prioritize by urgency × importance, not just recency
  2. Context-Aware Drafts: Match tone/language to sender and relationship
  3. Actionable Outputs: Every email gets a clear next action (respond, delegate, archive)
  4. Batch Efficiency: Process similar emails together to reduce context switching
  5. Status Tracking: Maintain visibility into response pipeline to prevent dropped balls

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