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 cxcscmu/SkillLearnBench --skill travel-data-queryinggit clone --depth 1 https://github.com/cxcscmu/SkillLearnBenchWrote 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/cxcscmu/skilllearnbench/travel-data-querying)<a href="https://agentmods.dev/skills/cxcscmu/skilllearnbench/travel-data-querying"><img src="https://agentmods.dev/badge/skills/cxcscmu/skilllearnbench/travel-data-querying.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00025 | $0.00518 |
| Opus 5 | $0.00013 | $0.00259 |
| Sonnet 5 | $0.00005 | $0.00104 |
| Haiku 4.5 | $0.00003 | $0.00052 |
Grade A, and why
travel-data-querying scanned grade A with 0 findings 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 3d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Travel Data Querying
Dataset Structure
All data lives under /app/data/ with these files:
Cities
background/citySet_with_states.txt— Tab-separated:CityName\tStatebackground/citySet.txt— City names onlybackground/stateSet.txt— State names only
Restaurants
restaurants/clean_restaurant_2022.csv- Columns:
index, Name, City, Cuisines, Average Cost, Aggregate Rating - Cuisines is a comma-separated string (e.g., "Tea, Pizza, Indian, Seafood")
- Average Cost is per meal (numeric)
Accommodations
accommodations/clean_accommodations_2022.csv- Columns:
index, NAME, room type, price, minimum nights, review rate number, house_rules, maximum occupancy, city house_rulescontains constraints like "No pets", "No smoking", "No parties", "No children under 10", "No visitors"- Price is per night
Attractions
attractions/attractions.csv- Columns:
Name, Latitude, Longitude, Address, Phone, Website, City
Distances
googleDistanceMatrix/distance.csv- Columns:
origin, destination, cost, duration, distance costcolumn is empty for driving (only populated for flights)- Duration is human-readable (e.g., "3 hours 11 mins")
- Distance in km
Flights
flights/clean_Flights_2022.csv— Not used when flights are excluded
Querying Patterns
Find cities in a state
grep -i "ohio" data/background/citySet_with_states.txt
Find restaurants by city and cuisine
grep -i "cleveland" data/restaurants/clean_restaurant_2022.csv | grep -i "italian"
Find pet-friendly accommodations (exclude "No pets")
grep -i "cleveland" data/accommodations/clean_accommodations_2022.csv | grep -iv "no pets"
Find driving distances between cities
grep -E "^Cleveland,Dayton," data/googleDistanceMatrix/distance.csv
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.
- 3d ago First seen · 64 lines · 25 tokens per session scan A 2209c8b7290d
travel-data-querying is a skill published in the GitHub repository cxcscmu/SkillLearnBench (83 stars, last pushed 1mo ago), licensed MIT. It adds 25 tokens to every session and 518 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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