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aashariaashari/ai-agent-skills/skills/apple-mail/mail-action-items/SKILL.md

mail-action-items

Skill7 starsChanged 9 months agoMITView on GitHub

Extract action items, tasks, and to-dos from recent emails. Scan email bodies for requests, deadlines, approvals needed, and follow-ups. Use when user wants to know what they need to do based on their email, or asks "what do I need to act on?" Arguments: optional time range (default: last 3 days) or account filter.

The file

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  • ≈1

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  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Look for action-item patterns in the body text:

    line 80

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Mail Action Items — Extract Tasks from Email

Time window: $ARGUMENTS (default: last 3 days)

Step 1: Find candidate emails with action signals

Subject-line signals

DB="$HOME/Library/Mail/V10/MailData/Envelope Index"
SINCE=$(($(date +%s) - 259200))  # 3 days default; adjust per $ARGUMENTS

sqlite3 "$DB" "
SELECT datetime(m.date_received,'unixepoch','localtime') as dt,
       s.subject, a.address as sender, a.comment as name,
       mb.url as mailbox, m.ROWID, m.read, m.is_urgent
FROM messages m
JOIN subjects  s  ON m.subject = s.ROWID
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 m.automated_conversation != 2
  AND mb.url NOT LIKE '%Spam%' AND mb.url NOT LIKE '%Trash%'
  AND mb.url NOT LIKE '%Sent%'
  AND (
    s.subject LIKE '%action required%'
    OR s.subject LIKE '%please review%'
    OR s.subject LIKE '%approval%'
    OR s.subject LIKE '%approve%'
    OR s.subject LIKE '%sign off%'
    OR s.subject LIKE '%deadline%'
    OR s.subject LIKE '%due%'
    OR s.subject LIKE '%RSVP%'
    OR s.subject LIKE '%respond by%'
    OR s.subject LIKE '%feedback%'
    OR s.subject LIKE '%request%'
    OR m.is_urgent = 1
    OR m.flagged = 1
  )
ORDER BY m.is_urgent DESC, m.date_received DESC;" 2>/dev/null

Urgent/flagged unread (always surface)

sqlite3 "$DB" "
SELECT datetime(m.date_received,'unixepoch','localtime') as dt,
       s.subject, a.address as sender, m.ROWID
FROM messages m
JOIN subjects s ON m.subject = s.ROWID
JOIN addresses a ON m.sender = a.ROWID
JOIN mailboxes mb ON m.mailbox = mb.ROWID
WHERE m.date_received >= ${SINCE}
  AND m.read = 0 AND m.deleted = 0
  AND m.automated_conversation != 2
  AND m.unsubscribe_type = 0
  AND mb.url NOT LIKE '%Spam%' AND mb.url NOT LIKE '%Trash%'
  AND mb.url NOT LIKE '%Sent%'
ORDER BY m.date_received DESC;" 2>/dev/null

Step 2: Read bodies and extract action items

For each candidate email, parse the body:

python3 ~/.claude/skills/_mail-shared/parser.py <ROWID1> <ROWID2> ...

Look for action-item patterns in the body text:

  • "Please [verb]..." → direct request
  • "Could you..." / "Can you..." → request
  • "By [date]" / "Before [date]" / "Due [date]" → deadline
  • "Let me know..." → response expected
  • "Your approval is needed" / "Please approve" → approval required
  • "Next steps:" / "Action items:" / "TODO:" → explicit task lists
  • "Waiting on you" / "Pending your" → you're the blocker
  • Meeting notes with "Suggested next steps" or your name + "will"

Step 3: Deduplicate and prioritize

  • Group by sender/thread
  • Prioritize: overdue deadlines > urgent flagged > approval requests > general requests
  • For Jira/project management alerts, extract ticket ID and description

Output Format

Action Items from Your Email (last 3 days)

For each item:

  • Task description — from [Sender], received [date]
    • Context: [1-line summary from email body]
    • Deadline: [if mentioned]

Group by: Overdue → Today → This week → No deadline Mark items from unread emails with [UNREAD].

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