A smart email analysis tool that transforms inbox clutter into actionable health metrics using weather metaphors and debt scoring.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install email-intelligence
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install email-intelligence using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Email Intelligence is a sophisticated analytical skill designed for Openclaw Skills that provides a deep dive into your inbox health. It goes beyond simple unread counts by employing creative weather metaphors—ranging from Calm Seas to Storm Warnings—to represent the current state of your digital communication.
By integrating with the himalaya CLI, this skill classifies messages into automated alerts, newsletters, notifications, and human interactions, allowing users to visualize their actual workload. The core philosophy is to treat the inbox as a living system, helping developers and professionals identify email debt and prioritize human connection over automated noise. This makes it an essential addition for those looking to enhance their workflow with Openclaw Skills.
To get started with this skill for Openclaw Skills, ensure you have the himalaya CLI installed and configured with IMAP access.
# Ensure Python 3.6+ and himalaya CLI are installed
# Perform a basic analysis for the last 7 days
python3 scripts/email_classify.py
# Analyze a 14-day window and output results in JSON format
python3 scripts/email_classify.py --days 14 --format json
The skill organizes data into several logical components to provide a clear overview of inbox state:
| Metric | Description | Data Type |
|---|---|---|
| Weather | Current inbox state (Calm Seas to Storm Warning) | Object (Level, Emoji, Description) |
| Categories | Tally of Automated, Newsletter, Notification, and Human mail | Object (Integers) |
| Debt Score | Weighted index of unread human emails (0-100 scale) | Integer |
| Ghost Report | List of unread human emails sorted by wait time | Array of Objects |
| Signal/Noise | Percentage of human vs. automated content | Object (Ratio, Percentage) |
| Time Cost | Estimated minutes required to process the inbox | Object (Minutes, Formatted String) |
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