← Back to Skills Marketplace
mickmicksh

Lap Airport Nearest Relevant

by mickmicksh · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
121
Downloads
0
Stars
1
Active Installs
1
Versions
Install in OpenClaw
/install lap-airport-nearest-relevant
Description
Airport Nearest Relevant API skill. Use when working with Airport Nearest Relevant for reference-data. Covers 1 endpoint.
README (SKILL.md)

Airport Nearest Relevant

API version: 1.1.2

Auth

No authentication required.

Base URL

https://test.api.amadeus.com/v1

Setup

  1. No auth setup needed
  2. GET /reference-data/locations/airports -- verify access

Endpoints

1 endpoints across 1 groups. See references/api-spec.lap for full details.

reference-data

Method Path Description
GET /reference-data/locations/airports Returns a list of relevant airports near to a given point.

Common Questions

Match user requests to endpoints in references/api-spec.lap. Key patterns:

  • "List all airports?" -> GET /reference-data/locations/airports

Response Tips

  • Check response schemas in references/api-spec.lap for field details

CLI

# Update this spec to the latest version
npx @lap-platform/lapsh get airport-nearest-relevant -o references/api-spec.lap

# Search for related APIs
npx @lap-platform/lapsh search airport-nearest-relevant

References

  • Full spec: See references/api-spec.lap for complete endpoint details, parameter tables, and response schemas

Generated from the official API spec by LAP

Usage Guidance
Before installing, verify these points: 1) Confirm whether the referenced Amadeus endpoint actually requires an API key or other auth — the SKILL.md claims 'No authentication required' which is uncommon for that host. 2) Inspect the referenced 'references/api-spec.lap' (or fetch the official Amadeus spec) to confirm parameter and auth requirements. 3) If you or the agent will run the suggested 'npx @lap-platform/lapsh' commands, be aware npx fetches remote code from npm at runtime; only run that if you trust the package and its publisher. 4) Because the skill source/homepage are unknown, consider testing calls manually (curl/postman) against the API in a controlled environment before allowing autonomous agent use, and avoid sending any sensitive or unrelated data to the endpoint. If the owner or spec can confirm 'no auth required' and provide a canonical source, that would increase confidence.
Capability Analysis
Type: OpenClaw Skill Name: lap-airport-nearest-relevant Version: 1.0.0 The skill bundle provides documentation and instructions for an AI agent to interact with the Amadeus Airport Nearest Relevant API (test.api.amadeus.com). It contains no executable code, suspicious prompt-injection instructions, or indicators of malicious intent, focusing solely on API endpoint definitions and standard CLI usage for spec management.
Capability Assessment
Purpose & Capability
Name/description, endpoint list, and base URL align with an airport-reference API skill. However the base URL is a commercial Amadeus test host (https://test.api.amadeus.com/v1) while the skill declares 'No authentication required' and requires no API key — that mismatch is suspicious and should be verified.
Instruction Scope
SKILL.md is instruction-only and stays narrowly focused on the single endpoint and where to find the API spec. It does instruct the agent to perform GET /reference-data/locations/airports and to use npx commands to fetch specs; it does not request reading unrelated files or credentials. The guidance to 'verify access' is vague and gives the agent broad discretion on how to call the API.
Install Mechanism
There is no install spec (instruction-only), so nothing will be written to disk by the skill itself. Note: the README suggests using 'npx @lap-platform/lapsh' — running npx will download and execute code from npm at runtime, which is a separate risk if the agent actually executes those commands.
Credentials
The skill requests no environment variables or credentials. Given the Amadeus base URL, it's common for that API to require client credentials; the absence of any declared auth or env vars conflicts with the likely real-world requirements of the API and could indicate an incomplete or inaccurate spec.
Persistence & Privilege
The skill does not request 'always: true' and has normal invocation settings. It does not declare any persistent configuration or system-level modifications.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install lap-airport-nearest-relevant
  3. After installation, invoke the skill by name or use /lap-airport-nearest-relevant
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of lap-airport-nearest-relevant skill. - Provides access to the Airport Nearest Relevant API (v1.1.2). - Supports a single endpoint to list relevant airports near a given point. - No authentication is required. - Includes usage setup instructions and common question matching. - Reference documentation and CLI tips included.
Metadata
Slug lap-airport-nearest-relevant
Version 1.0.0
License MIT-0
All-time Installs 1
Active Installs 1
Total Versions 1
Frequently Asked Questions

What is Lap Airport Nearest Relevant?

Airport Nearest Relevant API skill. Use when working with Airport Nearest Relevant for reference-data. Covers 1 endpoint. It is an AI Agent Skill for Claude Code / OpenClaw, with 121 downloads so far.

How do I install Lap Airport Nearest Relevant?

Run "/install lap-airport-nearest-relevant" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Lap Airport Nearest Relevant free?

Yes, Lap Airport Nearest Relevant is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Lap Airport Nearest Relevant support?

Lap Airport Nearest Relevant is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Lap Airport Nearest Relevant?

It is built and maintained by mickmicksh (@mickmicksh); the current version is v1.0.0.

💬 Comments