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Email Intelligence

作者 Paul Frederiksen · GitHub ↗ · v1.0.0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install email-intelligence
功能描述
Analyze email inbox health with weather metaphors, spam/signal classification, email debt scoring, and ghost detection. Use when user asks about inbox status...
使用说明 (SKILL.md)

Email Intelligence

Analyze your email inbox health using creative weather metaphors, intelligent classification, debt scoring, and ghost detection. Transform overwhelming inbox analysis into clear, actionable insights.

When to Use

Use this skill when the user asks about:

  • Inbox status or health
  • Email overwhelm or management
  • Who they're "ghosting" (ignoring responses to)
  • Time cost of processing their inbox
  • Signal vs noise in their email
  • Email debt or backlog

Requirements

  • himalaya CLI configured with IMAP access
  • Python 3.6+
  • The configured email account should have standard folder names (INBOX, Archive)

Quick Usage

# Basic analysis (last 7 days)
python3 scripts/email_classify.py

# Extended analysis (last 14 days)
python3 scripts/email_classify.py --days 14

# JSON output for integration
python3 scripts/email_classify.py --format json

Weather System

The inbox "weather" is determined by the number of human emails in your INBOX that need responses:

  • 🌊 Calm Seas (0-2): Inbox is peaceful and manageable
  • 🍃 Light Breeze (3-5): A few emails need attention, nothing urgent
  • 🌬️ Choppy Waters (6-10): Multiple emails require responses
  • ⛵ Small Craft Advisory (11-20): Many people waiting for replies
  • ⛈️ Storm Warning (21+): Inbox is overwhelming, needs immediate attention

Email Classification

Emails are automatically classified into four categories:

🤖 Automated

  • Sender contains: noreply, no-reply, donotreply, notifications@, alerts@
  • Subject contains: unsubscribe, automatic, auto-generated
  • Time cost: 0 minutes (can be safely ignored)

📰 Newsletter

  • From domains: substack.com, email., marketing., updates@
  • Subject contains: newsletter, digest, weekly, monthly, roundup
  • Time cost: 1 minute each (skim or archive)

🔔 Notification

  • From services: github, slack, jira, linear, aws, google, microsoft, etc.
  • Time cost: 30 seconds each (quick action/acknowledgment)

👥 Human

  • Everything else (actual people writing)
  • Time cost: 3 minutes each (requires thoughtful response)

Metrics Explained

Email Debt Score (0-100)

Calculated based on unseen human emails in your INBOX, weighted by age:

  • \x3C 1 day old: 1 point each
  • 1-3 days old: 3 points each
  • 3-7 days old: 5 points each
  • 7+ days old: 10 points each

Score meanings:

  • 0-30: 🟢 Great job! Inbox under control
  • 31-60: 🟡 Getting busy. Consider tackling some replies
  • 61-100: 🔴 High debt! Many emails waiting for responses

Signal-to-Noise Ratio

Percentage of emails that are from humans (signal) vs automated/newsletter/notification (noise).

Higher ratio = more meaningful email, less spam/clutter.

Ghost Report

Shows up to 5 people you're "ghosting" (human emails you haven't read), sorted by how long they've been waiting. Helps prioritize who needs responses most urgently.

Time Investment

Estimates how much time you'll need to process your current inbox based on email types and their typical processing times.

Output Formats

Text Format (Default)

Human-readable report with weather, debt score, signal/noise analysis, ghost report, and time estimates. Perfect for quick status updates or daily reviews.

JSON Format

Structured data for integration with other tools, APIs, or dashboards:

{
  "weather": {
    "level": "breeze",
    "emoji": "🍃", 
    "description": "Light Breeze - A few emails need attention...",
    "humanCount": 4
  },
  "categories": {
    "automated": 15,
    "newsletter": 8,
    "notification": 12,
    "human": 4
  },
  "debtScore": 18,
  "ghostReport": [...],
  "signalNoiseRatio": {
    "ratio": 0.103,
    "percentage": "10%"
  },
  "timeCost": {
    "minutes": 18,
    "formatted": "18 minutes"
  }
}

Integration Tips

Dashboard Integration

The JSON output is designed for easy integration into dashboards or status displays. The weather metaphor makes it intuitive for users to understand their inbox state at a glance.

Automation

Run periodically (via cron) to track inbox health trends over time. The debt score is particularly useful for identifying when inbox maintenance is needed.

Alerts

Set up alerts when:

  • Weather reaches "Storm Warning" level
  • Debt score exceeds 60
  • Ghost report shows people waiting >5 days

Troubleshooting

No emails found

  • Verify himalaya CLI is configured: himalaya envelope list -f INBOX --page-size 1
  • Check folder names match your email provider (some use "Inbox" vs "INBOX")

Classification seems wrong

The classification uses heuristics based on sender patterns and subject lines. You can modify the patterns in the script for your specific needs.

Slow performance

  • Reduce the --days parameter to analyze fewer emails
  • The script fetches up to 200 emails from Archive - adjust page_size in the code if needed

Philosophy

Email Intelligence treats your inbox as a living system with its own weather patterns and health metrics. Rather than just counting unread emails, it helps you understand:

  • What actually needs your attention (humans vs bots)
  • How "behind" you are (debt score)
  • Who you might be accidentally ignoring (ghost report)
  • How much time you're really looking at (time cost)

The weather metaphor makes inbox status intuitive and actionable - you know to "batten down the hatches" when a storm is brewing, but you can relax when the seas are calm.

Use this skill to transform inbox anxiety into clear, prioritized action plans.

安全使用建议
This skill appears to do what it claims: it uses the himalaya CLI to read your mailbox and analyzes messages locally, producing human-readable or JSON reports. Before installing or allowing the agent to run it autonomously: (1) confirm you have the himalaya CLI configured and understand which account it will access (IMAP credentials are stored in himalaya, not this skill), (2) review the included script locally — it prints sender/subject/date and may surface sensitive metadata, (3) note the registry metadata did not declare the himalaya dependency (an honesty/packaging mismatch), and (4) because the owner/homepage are unknown, prefer running the script yourself on sample data or in a controlled environment rather than granting broad autonomous access to your agent. If you want extra caution, run python3 scripts/email_classify.py locally and inspect outputs before enabling the skill for automated runs.
功能分析
Type: OpenClaw Skill Name: email-intelligence Version: 1.0.0 The skill bundle is classified as benign. The `SKILL.md` provides clear instructions and descriptions without any prompt injection attempts. The `scripts/email_classify.py` script securely executes the `himalaya` CLI tool using `subprocess.run` with a list of arguments, preventing shell injection. The script's actions are directly aligned with its stated purpose of analyzing email inbox health and do not involve data exfiltration, unauthorized remote control, persistence mechanisms, or access to unrelated sensitive files. It relies on the user having `himalaya` configured, but the script itself introduces no new vulnerabilities or malicious behavior.
能力评估
Purpose & Capability
The skill's name/description (inbox analysis) matches what the code does: it calls the himalaya CLI to read mail, classifies messages, computes scores, and prints structured output. However, the registry metadata lists no required binaries while SKILL.md explicitly requires the himalaya CLI — this metadata omission is an inconsistency that could mislead users about what will run.
Instruction Scope
SKILL.md and the script stick to inbox analysis: discovering folders, calling himalaya to list envelopes, classifying emails, and emitting text/JSON reports. The script reads email metadata (senders, subjects, dates, flags) and will include sender email/subject in outputs (expected for this purpose). There are no instructions or code paths that read unrelated files, other services, or send data to external endpoints.
Install Mechanism
No install spec (instruction-only plus an included Python script). No downloads or archive extraction. Risk is low because the code runs locally and depends on an already-installed himalaya CLI and Python.
Credentials
The skill requests no environment variables or external credentials in the manifest; it relies on the user's existing himalaya/IMAP configuration to access mail. That is proportionate to the described functionality. There are no unrelated credential requests.
Persistence & Privilege
always is false and there is no install step that attempts to persist or modify other skills or system-wide settings. Note: as with any skill that can be invoked autonomously, if the agent is allowed to run skills without explicit user prompts it could read email via himalaya; that's a platform-level policy consideration rather than a problem in this skill's code.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install email-intelligence
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /email-intelligence 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release: inbox weather, email debt score, ghost report, signal-to-noise ratio, time cost estimate, auto-discover folders
元数据
Slug email-intelligence
版本 1.0.0
许可证
累计安装 1
当前安装数 1
历史版本数 1
常见问题

Email Intelligence 是什么?

Analyze email inbox health with weather metaphors, spam/signal classification, email debt scoring, and ghost detection. Use when user asks about inbox status... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 544 次。

如何安装 Email Intelligence?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install email-intelligence」即可一键安装,无需额外配置。

Email Intelligence 是免费的吗?

是的,Email Intelligence 完全免费(开源免费),可自由下载、安装和使用。

Email Intelligence 支持哪些平台?

Email Intelligence 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Email Intelligence?

由 Paul Frederiksen(@pfrederiksen)开发并维护,当前版本 v1.0.0。

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