Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add borski/travel-hacking-toolkit --skill wikipedia-airportsgit clone --depth 1 https://github.com/borski/travel-hacking-toolkitWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/borski/travel-hacking-toolkit/wikipedia-airports)<a href="https://agentmods.dev/skills/borski/travel-hacking-toolkit/wikipedia-airports"><img src="https://agentmods.dev/badge/skills/borski/travel-hacking-toolkit/wikipedia-airports/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/borski/travel-hacking-toolkit/wikipedia-airports"><img src="https://agentmods.dev/badge/skills/borski/travel-hacking-toolkit/wikipedia-airports.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00041 | $0.01279 |
| Opus 5 | $0.00020 | $0.00639 |
| Sonnet 5 | $0.00008 | $0.00256 |
| Haiku 4.5 | $0.00004 | $0.00128 |
Grade A, and why
wikipedia-airports scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s "https://en.wikipedia.org/w/api.php?action=query&list=search&srsearch=SAN+airport&format=json" \ How it starts
The opening of the file, as written. The whole thing — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.
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.
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:
curl -Ls "https://en.wikipedia.org/wiki/San_Diego_International_Airport"
3. Look for route sections
Search for headings like:
Airlines and destinationsDestinationsPassengerAirlines
Example:
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:
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 156 lines · 41 tokens per session scan A d5fd52672c6e
wikipedia-airports is a skill published in the GitHub repository borski/travel-hacking-toolkit (659 stars, last pushed 4d ago), licensed MIT. It adds 41 tokens to every session and 1,279 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
docs-builder
Reorg a docs corpus, split an oversized doc, search it, keep pages current, index them.
live-canvas
Conduct design interviews, generate UI variations, and collect live click-to-annotate feedback that streams into the session so edits land without leaving the browser. Use when the user wants rapid iterative UI refinement, not just batched feedback.
remember
Consolidate stashes + friction into project memory.
branch-review
Review a branch before merge [target] [level].
root-cause
Use when any test fails, bug appears, or behaviour surprises you, before proposing a fix - find the cause and prove it, by reading real evidence, tracing bad values back to their origin, comparing against a working case, and testing one hypothesis at a time.
ship
Mechanical pre-deploy gate — tests, build, tree state.