---
name: mail-action-items-eec50b5bf1cf
description: >-
  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.
disable-model-invocation: false
user-invocable: true
allowed-tools: Bash
metadata:
  openclaw:
    requires:
      bins: [sqlite3, python3]
---

# 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
```bash
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)
```bash
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:
```bash
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].


---
Source attribution: aashari
Original project: https://github.com/aashari/ai-agent-skills/blob/42445bdfaaf6d2dddcd74ff5c3e6fd82c4287867/skills/apple-mail/mail-action-items/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-action-items/SKILL.md
Attribution basis: Source repository record

Fields of work: Sales, Operations, Project & Program Management
Roles: Customer Success Manager, Operations Manager, Project Manager
Specialties: Specialty not specified
Tools: Sqlite3, Python3
Country applicability: Country not specified
Classification basis: Source category, role and specialization labels
Instruction SHA-256: affab082f63849d3503e78ce653ae6ed267336d1ae8d38f381cc7a88671d7f68