Notamify for Openclaw

A professional aviation intelligence tool for retrieving, interpreting, and analyzing global NOTAMs via the Notamify Python SDK.

damians21
v1.0.2
Apr 3, 2026
0
778
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install notamify

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

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).

Prefer to download?

Get the raw skill files in a ZIP archive.

What is Notamify?

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.

Notamify Use Cases

  • Monitoring real-time airport closures and hazards for flight planning.
  • Investigating historical airport conditions for compliance or incident analysis.
  • Performing geospatial searches for NOTAMs along a specific flight path or coordinate radius.
  • Generating automated, structured flight briefings between origin and destination airports.
  • Filtering aviation notices by specific types such as runway restrictions or navaid unserviceability.

How Notamify Works

  1. Identify the target airports and convert their names into standard 4-character ICAO codes.
  2. Select the appropriate query type, including active, nearby, historical, or full briefing modes.
  3. Execute a Python-based script using the notamify-sdk to interface with the Notamify API.
  4. Process the returned NOTAM objects, which include both the raw ICAO message and an AI-interpreted summary.
  5. Present the aviation data to the user, highlighting the most critical safety information and operational impacts.

Notamify Setup

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.

Notamify Data Schema & Taxonomy

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).

Notamify Advanced Features

  • AI-powered interpretation that extracts the core meaning from complex ICAO-formatted text.
  • Asynchronous flight briefing generation for complex routes including aircraft type and runway specifics.
  • Advanced filtering using Q-codes, interpretation subcategories, and specific hazard effects.
  • Historical archive access for auditing NOTAMs active at any point in the past.
  • Support for multiple authentication methods, including environment variables and local configuration files.

SKILL.md


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