# Gmail Analyze

> Analyze Gmail inbox patterns to identify high-volume senders and suggest filter rules. Use when organizing email, creating automation rules, or understanding inbox composition. Works with personal Gmail accounts via gog CLI. Use when this capability is needed.

- Skill: `tomevault-io/gmail-analyze` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add tomevault-io/gmail-analyze`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/gmail-analyze/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Productivity
- Author: tomevault-io (https://skillmd.com/u/tomevault-io)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tomevault-io/gmail-analyze

---


# Gmail Inbox Analyzer

Analyze inbox patterns and suggest intelligent filter rules using Pareto analysis.

## Prerequisites Check

First, verify gog CLI is authenticated:

```bash
gog auth status
```

If not authenticated, guide the user to run:
```bash
gog auth add their.email@gmail.com
```

## Analysis Workflow

### Step 1: Fetch Recent Emails

Fetch emails from the specified time period (default: 30 days):

```bash
gog gmail search 'newer_than:${DAYS}d' --json
```

Parse the JSON output to extract:
- `from` - Sender email
- `subject` - Email subject
- `date` - Received date
- `labelIds` - Applied labels

### Step 2: Pattern Analysis

Analyze the fetched emails to identify:

1. **Top Sender Domains** (Pareto: focus on top 20%)
   - Group emails by sender domain
   - Count frequency per domain
   - Identify domains with 5+ emails

2. **Sender Categories**
   - Newsletters: substack, mailchimp, newsletter, digest
   - Notifications: github, gitlab, jira, slack, notion
   - Shopping: amazon, ebay, order, shipping
   - Social: facebook, twitter, linkedin

3. **Volume Distribution**
   - Total emails analyzed
   - Emails per day average
   - Peak sending times

### Step 3: Generate Suggestions

For each high-volume pattern, suggest:

| Domain | Count | Suggested Label | Filter Criteria | Confidence |
|--------|-------|-----------------|-----------------|------------|
| substack.com | 45 | Newsletters | from:@substack.com | High |
| github.com | 32 | Notifications | from:@github.com | High |

### Step 4: Present Results

Output a formatted report:

```
## Inbox Analysis Report

**Period**: Last {days} days
**Total Emails**: {count}
**Unique Senders**: {unique}

### Top 10 Sender Domains

1. example.com - 142 emails (28%)
2. github.com - 89 emails (18%)
...

### Suggested Filters

| Priority | Pattern | Label | Est. Impact |
|----------|---------|-------|-------------|
| 1 | from:@newsletter.com | Newsletters | 45 emails/month |
| 2 | from:@github.com | Notifications | 32 emails/month |

### Recommended Actions

1. Create "Newsletters" label and filter
2. Create "Notifications" label with auto-archive
3. ...

Would you like me to create these filters? Use `/gmail-filter` to proceed.
```

## Arguments

- `$ARGUMENTS` - Number of days to analyze (default: 30)

## Example Usage

```
User: /gmail-analyze 60
```

Analyzes the last 60 days of email.

## Output Format

Always provide:
1. Summary statistics
2. Top senders table
3. Suggested filters with confidence levels
4. Clear next steps

## Error Handling

- If gog not installed: Provide installation instructions
- If not authenticated: Guide through OAuth setup
- If no emails found: Suggest widening the search period

---
> Converted and distributed by [TomeVault](https://tomevault.io/claim/corentinlumineau) — claim your Tome and manage your conversions.
<!-- tomevault:4.0:skill_md:2026-04-15 -->