Mail Top Senders

Mail Top Senders — Communication Frequency Analysis

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

Step 1: All senders ranked by volume

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)

# 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

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:

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 & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: aashari
• Source: aashari/ai-agent-skills
• License: MIT

Install and usage instructions live in the source repository linked above.