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Wikipedia Airports

Community
borski
wikipedia-airports

Discover destinations served from any airport via Wikipedia. Sanity-check whether an airline flies a specific route, find regional service that fare tools miss, identify late-split-return airport options.

Overview

Publisherborski
Repositorytravel-hacking-toolkit
Skill namewikipedia-airports
Stars
690
Forks
75
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by borski on GitHub. Read the source before you install it.

Installation

Install the Wikipedia Airports AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/borski/travel-hacking-toolkit/tree/main/plugins/travel-hacking-toolkit/skills/wikipedia-airports
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/borski/travel-hacking-toolkit.git /tmp/travel-hacking-toolkit
mkdir -p .claude/skills
cp -r /tmp/travel-hacking-toolkit/plugins/travel-hacking-toolkit/skills/wikipedia-airports .claude/skills/wikipedia-airports
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Wikipedia Airports in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Wikipedia Airports on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Wikipedia Airports is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Wikipedia Airports

Use Wikipedia as a route discovery and sanity-check source for airport destinations. This is especially useful when:

  • an airport page has an Airlines and destinations section
  • an airline's own city-pair marketing pages confirm service patterns
  • flight search tools disagree about whether a route exists

Wikipedia is not a booking source and not a real-time schedule source. Use it to discover likely routes, then confirm them with airline or fare tools.

Best Use Cases

  • "What destinations does SAN serve?"
  • "Does Southwest fly SAN -> EUG?"
  • "What airports can I use for a late split return?"
  • "Which airline serves this small airport nonstop?"

Workflow

1. Resolve the airport page from an IATA code

Use Wikipedia search with the airport code plus the word airport.

bash
curl -s "https://en.wikipedia.org/w/api.php?action=query&list=search&srsearch=SAN+airport&format=json" \
  | jq '.query.search[0:5][] | {title}'

Usually the first result is the airport page, e.g. San Diego International Airport.

2. Fetch the page

Use the readable page HTML or the wikitext parse API.

bash
curl -s "https://en.wikipedia.org/w/api.php?action=parse&page=San_Diego_International_Airport&prop=wikitext&formatversion=2&format=json" \
  | jq -r '.parse.wikitext'

Or fetch the rendered page:

bash
curl -Ls "https://en.wikipedia.org/wiki/San_Diego_International_Airport"

3. Look for route sections

Search for headings like:

  • Airlines and destinations
  • Destinations
  • Passenger
  • Airlines

Example:

bash
curl -s "https://en.wikipedia.org/w/api.php?action=parse&page=San_Diego_International_Airport&prop=wikitext&formatversion=2&format=json" \
  | jq -r '.parse.wikitext' \
  | rg -n "Airlines and destinations|Destinations|Passenger|Southwest|Eugene|Portland"

4. Treat airline city-pair pages as a second source

If the airport page is incomplete, use airline route pages to validate the pattern.

Examples:

bash
curl -Ls "https://www.southwest.com/en/flights/flights-from-portland-or-to-san-diego" | rg "PDX|SAN|Portland|San Diego"
curl -Ls "https://www.southwest.com/en/flights/flights-from-portland-or-to-orange-county-santa-ana" | rg "PDX|SNA|Portland|Orange County"

This is especially useful for Southwest because:

  • it is missing from most GDS sources
  • route existence is often easier to verify from marketing pages than from award/cash APIs

5. Then confirm with fare tools

After Wikipedia suggests the route exists:

  1. Check cash pricing with SerpAPI, Kiwi, Skiplagged, or Duffel (if supported)
  2. Check Southwest separately when needed
  3. Prefer airline/fare-tool evidence over Wikipedia if they disagree

Decision Rules

Use Wikipedia to answer:

  • whether an airport likely has service to a destination
  • which airlines appear to serve a city pair
  • whether a small airport is worth searching

Do NOT use Wikipedia to answer:

  • exact daily schedules
  • whether a flight is operating on a specific date
  • current fares
  • award availability

Example: SAN and Southwest to EUG

If the SAN airport page or related route references indicate Southwest serves Eugene, treat that as a lead, not final proof.

Then validate with:

  1. Southwest route pages or booking pages
  2. Google Flights / SerpAPI
  3. Southwest-specific search if available

This skill is most valuable when it tells you "search this route, don't assume it doesn't exist."

Useful Patterns

Airport page lookup by IATA code

bash
CODE=SAN
curl -s "https://en.wikipedia.org/w/api.php?action=query&list=search&srsearch=${CODE}+airport&format=json" \
  | jq -r '.query.search[0].title'

Pull likely destination section lines

bash
PAGE="San_Diego_International_Airport"
curl -s "https://en.wikipedia.org/w/api.php?action=parse&page=${PAGE}&prop=wikitext&formatversion=2&format=json" \
  | jq -r '.parse.wikitext' \
  | rg -n "Airlines and destinations|Destinations|Alaska|Southwest|United|Delta|Eugene|Portland|Redmond"

Search for an airline + destination on the page

bash
PAGE="San_Diego_International_Airport"
curl -s "https://en.wikipedia.org/w/api.php?action=parse&page=${PAGE}&prop=wikitext&formatversion=2&format=json" \
  | jq -r '.parse.wikitext' \
  | rg -n "Southwest|Eugene|EUG"

Notes

  • Wikipedia pages vary wildly in quality. Some airports have complete route tables; others are stale.
  • Small airports are often better maintained than airline route databases for simple "does this exist?" checks.
  • When Wikipedia and fare tools disagree, trust the fare/schedule sources for booking decisions.
  • Use this skill as a discovery and cross-check tool, not a source of truth.

Frequently asked questions

What does the Wikipedia Airports AI skill do?

Discover destinations served from any airport via Wikipedia. Sanity-check whether an airline flies a specific route, find regional service that fare tools miss, identify late-split-return airport options.

Why use Wikipedia Airports on TypingMind?

Because you install it once and use it with any model. Wikipedia Airports is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Wikipedia Airports in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/borski/travel-hacking-toolkit/tree/main/plugins/travel-hacking-toolkit/skills/wikipedia-airports. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Wikipedia Airports?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Wikipedia Airports?

As many as you like. As long as a model supports skills, you can use Wikipedia Airports with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Wikipedia Airports AI skill free?

Yes. It is published on GitHub by borski under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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