- name
- email-summarizer
- description
- Email summary and contact profiling skill. Fetch emails from an IMAP mailbox or parse local exports (.pst / .mbox / .msg), build a contact profile report (HTML + Excel), and optionally send it via email. Trigger when user says "summarize my emails", "check recent emails", "analyze my contacts", "profile email contacts", "parse pst file", "analyze outlook export", "send contact report", etc.
- env
- EMAIL_USER
- description
- Your email address. Used for IMAP login and SMTP sender.
- required
- false
- example
- you@163.com
- EMAIL_PASS
- description
- IMAP/SMTP app password (NOT your login password). Generate in mailbox settings under POP3/SMTP/IMAP.
- required
- false
- example
- your-app-password
Email Summarizer + Contact Profiler
Three independent stages — run any subset depending on what you need:
[Data Source] [Analysis] [Delivery]
fetch_imap.py ──→ ──→
parse_file.py ──→ build_report.py ──→ send_report.py
→ .html + .xlsxEach stage reads from / writes to files (or stdin/stdout), so they compose freely.
Installation
# Python dependencies
pip install -r requirements.txt
# Node.js dependency (only for native .pst parsing)
cd scripts && npm install && cd ..Script Reference
Stage 1 — Data Source
fetch_imap.py — Fetch emails from a live IMAP mailbox
export EMAIL_USER=you@163.com
export EMAIL_PASS=your-app-password
# Fetch last 7 days (inbox only) → emails.json
python3 scripts/fetch_imap.py --days 7 --output emails.json
# Fetch a date range, inbox + sent
python3 scripts/fetch_imap.py --since 2026-03-01 --until 2026-03-28 \
--with-sent --preset 163 --output emails.json
# Pipe directly to build_report.py (no intermediate file)
python3 scripts/fetch_imap.py --days 30 | python3 scripts/build_report.py --output report| Flag | Default | Description | ||||
|---|---|---|---|---|---|---|
--days N | 7 | Fetch last N days. Ignored if --since is set. | ||||
--since DATE | — | Start date inclusive (YYYY-MM-DD) | ||||
--until DATE | — | End date exclusive (YYYY-MM-DD, default: today) | ||||
--max N | 200 | Max emails per folder | ||||
--folder NAME | INBOX | Inbox folder name | ||||
--preset NAME | 163 | Mailbox preset: 163 \ | qq \ | exmail \ | gmail \ | outlook |
--with-sent | off | Also fetch Sent folder (recommended for relationship analysis) | ||||
--output FILE | stdout | Write JSON to file; prints to stdout if omitted |
Supported presets:
| Preset | IMAP Server | Sent folder |
|---|---|---|
163 | imap.163.com:993 | 已发送 |
qq | imap.qq.com:993 | Sent Messages |
exmail | imap.exmail.qq.com:993 | Sent Messages |
gmail | imap.gmail.com:993 | [Gmail]/Sent Mail |
outlook | outlook.office365.com:993 | Sent Items |
parse_file.py — Parse a local email export
# Parse a .pst file (native engine, no system install needed)
python3 scripts/parse_file.py --pst ~/Downloads/archive.pst --output emails.json
# Parse a .mbox file (inbox + sent)
python3 scripts/parse_file.py --mbox Inbox.mbox --sent-mbox Sent.mbox --output emails.json
# Parse a folder of .msg files, filter by date
python3 scripts/parse_file.py --msg-dir ./exported/ --since 2026-01-01 --output emails.json
# Pipe to build_report.py
python3 scripts/parse_file.py --pst archive.pst | python3 scripts/build_report.py --output report| Flag | Default | Description | ||
|---|---|---|---|---|
--pst FILE | — | Outlook .pst archive | ||
--mbox FILE | — | Unix mbox file | ||
--msg-dir DIR | — | Folder of .msg files | ||
--sent-mbox FILE | — | Additional sent-items mbox (with --mbox) | ||
--pst-engine | auto | auto \ | native \ | readpst |
--days N | all | Only include last N days | ||
--since DATE | — | Start date inclusive (YYYY-MM-DD) | ||
--until DATE | — | End date exclusive (YYYY-MM-DD) | ||
--max N | 500 | Max emails to load | ||
--output FILE | stdout | Write JSON to file; prints to stdout if omitted |
PST engines:
| Engine | Flag | Requires |
|---|---|---|
| Native (default) | --pst-engine native | cd scripts && npm install |
| Readpst | --pst-engine readpst | apt install pst-utils or brew install libpst |
| Auto | --pst-engine auto | Tries native first, falls back to readpst |
Stage 2 — Analysis
build_report.py — Analyse emails → HTML + Excel report
# From a file
python3 scripts/build_report.py --input emails.json --output report
# Specify owner explicitly (when analysing someone else's PST)
python3 scripts/build_report.py --input emails.json --output report \
--owner xiang-xiang.hu@connect.polyu.hk
# From stdin (piped from Stage 1)
python3 scripts/fetch_imap.py --days 30 | python3 scripts/build_report.py --output report| Flag | Default | Description |
|---|---|---|
--input FILE | stdin | Path to emails JSON from Stage 1 |
--output PREFIX | contact_report | Output path prefix. Writes <prefix>.html and <prefix>.xlsx |
--owner EMAIL | auto-inferred | Mailbox owner address. Auto-detected if omitted. |
Output files:
<prefix>.html— self-contained HTML report (open in browser or attach to email)<prefix>.xlsx— Excel spreadsheet with the same data
Report columns: # / Preferred Name / Email / Company / Position / Subject Summary / Source / Emails (Recv/Sent)
Stage 3 — Delivery
send_report.py — Send report files via SMTP
export EMAIL_USER=you@163.com
export EMAIL_PASS=your-app-password
# Send HTML + Excel to a recipient
python3 scripts/send_report.py \
--html report.html --xlsx report.xlsx --to friend@example.com
# Send to yourself (EMAIL_USER)
python3 scripts/send_report.py --html report.html --xlsx report.xlsx
# HTML only (no attachment)
python3 scripts/send_report.py --html report.html --to friend@example.com
# Custom subject
python3 scripts/send_report.py --html report.html --subject "March Contact Report"| Flag | Default | Description | ||||
|---|---|---|---|---|---|---|
--html FILE | required | HTML file to use as email body | ||||
--xlsx FILE | — | Excel file to attach (optional) | ||||
--to ADDR | EMAIL_USER | Recipient address | ||||
--subject STR | auto | Email subject (auto-generated if omitted) | ||||
--preset NAME | 163 | SMTP preset: 163 \ | qq \ | exmail \ | gmail \ | outlook |
Private library modules (not standalone scripts)
| File | Provides |
|---|---|
_core.py | decode_header, parse_addr, get_domain, strip_html, html_esc, get_body |
_analyze.py | infer_owner, build_contacts, domain/company/position/name inference |
_render.py | build_report_html, build_excel, SMTP_MAP |
Complete workflow examples
A — IMAP mailbox → report → send to self
export EMAIL_USER=you@163.com
export EMAIL_PASS=your-app-password
python3 scripts/fetch_imap.py --days 30 --with-sent --output /tmp/emails.json
python3 scripts/build_report.py --input /tmp/emails.json --output /tmp/report
python3 scripts/send_report.py --html /tmp/report.html --xlsx /tmp/report.xlsx --preset 163B — PST file → report → send to someone
python3 scripts/parse_file.py --pst ~/Downloads/archive.pst --output /tmp/emails.json
python3 scripts/build_report.py --input /tmp/emails.json --output /tmp/report
EMAIL_USER=sender@163.com EMAIL_PASS=xxx \
python3 scripts/send_report.py --html /tmp/report.html --xlsx /tmp/report.xlsx \
--to recipient@example.comC — One-liner (pipe, no intermediate files)
python3 scripts/parse_file.py --pst archive.pst \
| python3 scripts/build_report.py --output /tmp/reportD — Report only, no email (open locally)
python3 scripts/parse_file.py --mbox Inbox.mbox --output /tmp/emails.json
python3 scripts/build_report.py --input /tmp/emails.json --output /tmp/report
# Open /tmp/report.html in a browserAI analysis templates
After loading the email JSON into the AI context, use the following templates:
Part A: 4-Dimension Email Summary
🔥 Part 1 — Important & Action Items
🚨 [URGENT] Subject — Sender — Date | Summary | Action | Deadline
⚡ [IMPORTANT] Subject — Sender — Date | Summary | Action
📌 [NOTE] Subject — Sender — Date | Summary
📊 Part 2 — Grouped by Sender / Topic
✅ Part 3 — To-Do List
📅 Part 4 — Timeline (YYYY-MM-DD Sender → Subject: summary)Part B: Contact Profile Analysis
Sort by total interactions. For each contact:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
👤 Rank #N | Name <email> Total: N (Recv: N / Sent: N)
🧑 Gender M/F/Unknown Confidence: H/M/L Basis: …
💼 Role … Basis: domain / signature / keywords
🔗 Relationship Colleague / Client / Institution / Stranger
Direction Mutual / Owner-initiated / Contact-initiated
📝 Topics • subject 1 • subject 2
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━Heat scale: 🔥 Heavy (≥10) · ⚡ Active (5–9) · 💬 Moderate (2–4) · 🌙 Light (1)
Notes
- Credentials are passed via environment variables — never hardcoded
- IMAP connections use readonly mode — emails are never modified or deleted
- Body text is truncated to 2000 characters per email
fetch_imap.pysends an RFC 2971 ID command required by 163/188 servers; harmless on others