---
name: mail-top-senders-0a450d3283e7
description: >-
  Show who sends the most email, communication frequency analysis, and relationship mapping. Use when user asks who emails them most, top contacts, communication patterns, or wants to understand their email social graph. Arguments: optional time range (default: last 90 days), account filter, or "humans only" to exclude automated senders.
disable-model-invocation: false
user-invocable: true
allowed-tools: Bash
metadata:
  openclaw:
    requires:
      bins: [sqlite3]
---

# Mail Top Senders — Communication Frequency Analysis

Analysis period: **$ARGUMENTS** (default: last 90 days)

## Step 1: All senders ranked by volume
```bash
DB="$HOME/Library/Mail/V10/MailData/Envelope Index"
SINCE=$(($(date +%s) - 7776000))  # 90 days

sqlite3 "$DB" "
SELECT a.address, a.comment as name,
       COUNT(*) as total,
       SUM(CASE WHEN m.read=0 THEN 1 ELSE 0 END) as unread,
       MIN(datetime(m.date_received,'unixepoch','localtime')) as first,
       MAX(datetime(m.date_received,'unixepoch','localtime')) as latest
FROM messages m
JOIN addresses a  ON m.sender  = a.ROWID
JOIN mailboxes mb ON m.mailbox = mb.ROWID
WHERE m.date_received >= ${SINCE}
  AND m.deleted = 0
  AND mb.url NOT LIKE '%Spam%' AND mb.url NOT LIKE '%Trash%'
  AND mb.url NOT LIKE '%Sent%'
GROUP BY a.address
ORDER BY total DESC
LIMIT 50;" 2>/dev/null
```

## Step 2: Separate humans from automated senders
Use `automated_conversation` and `unsubscribe_type` columns (more reliable than address-pattern matching):
- `automated_conversation = 0` + `unsubscribe_type = 0` → real humans
- `automated_conversation = 1` → transactional (Jira, Slack, alerts)
- `automated_conversation = 2` OR `unsubscribe_type > 0` → bulk/newsletters (noise)

```bash
# Human senders only (automated_conversation = 0, no unsubscribe header)
sqlite3 "$DB" "
SELECT a.address, a.comment as name, COUNT(*) as cnt
FROM messages m
JOIN addresses a ON m.sender = a.ROWID
JOIN mailboxes mb ON m.mailbox = mb.ROWID
WHERE m.date_received >= ${SINCE}
  AND m.deleted = 0
  AND mb.url NOT LIKE '%Spam%' AND mb.url NOT LIKE '%Sent%'
  AND m.automated_conversation = 0
  AND m.unsubscribe_type = 0
GROUP BY a.address ORDER BY cnt DESC LIMIT 20;" 2>/dev/null
```

## Step 3: Domain-level analysis
```bash
sqlite3 "$DB" "
SELECT substr(a.address, instr(a.address,'@')+1) as domain,
       COUNT(*) as cnt
FROM messages m
JOIN addresses a ON m.sender = a.ROWID
JOIN mailboxes mb ON m.mailbox = mb.ROWID
WHERE m.date_received >= ${SINCE}
  AND m.deleted = 0
  AND mb.url NOT LIKE '%Spam%'
GROUP BY domain ORDER BY cnt DESC LIMIT 20;" 2>/dev/null
```

## Step 4: Thread participation (two-way communication)
Find senders you also replied to — true relationships vs. one-way communication:
```bash
sqlite3 "$DB" "
SELECT a.address, COUNT(*) as received
FROM messages m
JOIN addresses a ON m.sender = a.ROWID
JOIN mailboxes mb ON m.mailbox = mb.ROWID
WHERE m.date_received >= ${SINCE} AND m.deleted=0
  AND mb.url NOT LIKE '%Sent%'
GROUP BY a.address
ORDER BY received DESC LIMIT 30;" 2>/dev/null
```

## Output Format
**Top Email Relationships — [PERIOD]**

**Most Frequent Human Contacts:**
| Rank | Name | Address | Emails Received | Unread |
|---|---|---|---|---|

**Top Automated Senders (noise):**
| Service | Count | Type |
|---|---|---|

**Top Domains:**
| Domain | Count |
|---|---|

Insight: note anyone with high unread rate (you receive a lot but don't read → de-prioritize subscription?).
Note anyone with very recent last email who you haven't read → potential missed message.


---
Source attribution: aashari
Original project: https://github.com/aashari/ai-agent-skills/blob/42445bdfaaf6d2dddcd74ff5c3e6fd82c4287867/skills/apple-mail/mail-top-senders/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 Ashari Tech

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: aashari
Original project: https://github.com/aashari/ai-agent-skills/blob/42445bdfaaf6d2dddcd74ff5c3e6fd82c4287867/skills/apple-mail/mail-top-senders/SKILL.md
Attribution basis: Source repository record

Fields of work: Sales, Marketing, Data & Analytics
Roles: Customer Success Manager, Marketing Analyst, Data Analyst
Specialties: Specialty not specified
Tools: Sqlite3
Country applicability: Country not specified
Classification basis: Source category, role and specialization labels
Instruction SHA-256: d7a135d77a8e51ab1013220fc281ec198a2b1043a4a7ef617735866d3963ee2a