A professional aviation intelligence tool for retrieving, interpreting, and analyzing global NOTAMs via the Notamify Python SDK.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install notamify
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 notamify using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Notamify is a specialized tool within the Openclaw Skills ecosystem designed for pilots, dispatchers, and aviation developers. It provides a robust interface to query Notices to Airmen (NOTAMs) for airports worldwide, transforming raw, often cryptic aviation messages into structured, actionable intelligence. By leveraging this skill, users can automate the monitoring of airport conditions, runway closures, and navigation hazards through their AI coding agent.
The skill goes beyond simple data retrieval by offering AI-driven interpretations. It classifies NOTAMs into specific categories such as aerodrome, airspace, or weather, and identifies affected elements like runways or taxiways. This makes Notamify an essential component for any aviation-focused workflow integrated with Openclaw Skills, ensuring that critical safety information is always accessible and easy to understand.
To get started with this skill, install the Python SDK in your environment:
pip install notamify-sdk
You must also obtain an API token from the Notamify API Manager and configure it as an environment variable for the Openclaw Skills agent to use:
export NOTAMIFY_TOKEN="your_api_key_here"
The SDK will automatically detect this token to authenticate your requests.
The skill organizes aviation data using structured NOTAM objects. Below is the primary data taxonomy:
| Field | Type | Description |
|---|---|---|
| notam_number | String | Unique identifier for the aviation notice. |
| icao_code | String | The 4-character airport code (e.g., KJFK, EGLL). |
| interpretation | Object | AI-generated summary, category, and affected elements. |
| valid_from/to | Datetime | The temporal validity window in UTC. |
| affected_elements | List | Specific assets impacted (e.g., RUNWAY, NAVAID, LIGHTING). |
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