Metadata

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 + .xlsx

Each 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 163

B — 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.com

C — One-liner (pipe, no intermediate files)

python3 scripts/parse_file.py --pst archive.pst \
  | python3 scripts/build_report.py --output /tmp/report

D — 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 browser

AI 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.py sends an RFC 2971 ID command required by 163/188 servers; harmless on others

email-summarizer

安装技能

Email Summarizer + Contact Profiler

Installation

Script Reference

Stage 1 — Data Source

`fetch_imap.py` — Fetch emails from a live IMAP mailbox

`parse_file.py` — Parse a local email export

Stage 2 — Analysis

`build_report.py` — Analyse emails → HTML + Excel report

Stage 3 — Delivery

`send_report.py` — Send report files via SMTP

Private library modules (not standalone scripts)

Complete workflow examples

A — IMAP mailbox → report → send to self

B — PST file → report → send to someone

C — One-liner (pipe, no intermediate files)

D — Report only, no email (open locally)

AI analysis templates

Part A: 4-Dimension Email Summary

Part B: Contact Profile Analysis

Notes

360 行为纵深安全审计引擎

email-summarizer

安装技能

Email Summarizer + Contact Profiler

Installation

Script Reference

Stage 1 — Data Source

fetch_imap.py — Fetch emails from a live IMAP mailbox

parse_file.py — Parse a local email export

Stage 2 — Analysis

build_report.py — Analyse emails → HTML + Excel report

Stage 3 — Delivery

send_report.py — Send report files via SMTP

Private library modules (not standalone scripts)

Complete workflow examples

A — IMAP mailbox → report → send to self

B — PST file → report → send to someone

C — One-liner (pipe, no intermediate files)

D — Report only, no email (open locally)

AI analysis templates

Part A: 4-Dimension Email Summary

Part B: Contact Profile Analysis

Notes

`fetch_imap.py` — Fetch emails from a live IMAP mailbox

`parse_file.py` — Parse a local email export

`build_report.py` — Analyse emails → HTML + Excel report

`send_report.py` — Send report files via SMTP