email-summarizer（电子邮件摘要器） Skills下载安装命令和教程

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手，先确认命令和权限，再让它执行。

请帮我安装这个 Agent Skill：email-summarizer（电子邮件摘要器）
来源仓库：https://github.com/momothemage/email-summarizer
安装命令：
openclaw skills install email-summarizer
安装前请先检查当前环境是否支持对应 CLI，并向我确认将要执行的命令、安装目录、联网范围和文件读写权限；确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill；本站只展示命令，不托管安装包，也不自动执行。

ClawHubOpenClaw

openclaw skills install email-summarizer

简介

从 IMAP 邮箱或本地 PST/Mbox 文件中提取邮件并生成联系人分析报告。

适合法务、审计或客户关系部门梳理历史沟通脉络。email-summarizer 属于开发类 Skill，可作为该场景下的辅助能力补充。
输出 HTML 格式的联系人档案，包含往来频率与话题分布。
涉及大容量数据处理，需确保运行环境具备足够内存资源。
建议在非工作时间运行长时间任务，避免影响实时响应速度。

SKILL.md

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

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明，方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用；具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

79.42%

按下载量换算1,499

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力，使用时可能读取或操作网页内容，需要在受控环境中确认权限边界。

安装前确认

本站仅展示第三方公开信息，不托管安装包，不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源，正式发布前建议补源仓库或其他目录站核验。

来源信息

GitHub 仓库

github.com

/momothemage/email-summarizer

SKILL.md 来源

clawhub.ai

/momothemage/email-summarizer

继续浏览同类 Skills

更多开发 Skills（21,746）返回 Skills 目录

上一个 Skill

email-smtp-send（电子邮件 smtp 发送）

email-smtp-send 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息，适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态，以及是否会触发联网、命令执行或文件读写。

下一个 Skill

email-template-generator（电子邮件模板生成器）

email-template-generator 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息，适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态，以及是否会触发联网、命令执行或文件读写。

email-summarizer（电子邮件摘要器）