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-itinerary-datagit 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-itinerary-data)<a href="https://agentmods.dev/skills/cxcscmu/skilllearnbench/travel-itinerary-data"><img src="https://agentmods.dev/badge/skills/cxcscmu/skilllearnbench/travel-itinerary-data/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/cxcscmu/skilllearnbench/travel-itinerary-data"><img src="https://agentmods.dev/badge/skills/cxcscmu/skilllearnbench/travel-itinerary-data.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 | $0.00031 | $0.00682 |
| Opus 5 | $0.00015 | $0.00341 |
| Sonnet 5 | $0.00006 | $0.00136 |
| Haiku 4.5 | $0.00003 | $0.00068 |
Grade A, and why
travel-itinerary-data 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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Travel Itinerary Data Querying
Dataset locations (relative to /app/data/)
| File | Key columns |
|---|---|
background/citySet_with_states.txt |
city TAB state — enumerate valid cities |
restaurants/clean_restaurant_2022.csv |
id, Name, City, Cuisines, Average Cost, Aggregate Rating |
accommodations/clean_accommodations_2022.csv |
id, NAME, room type, price, minimum nights, review rate number, house_rules, maximum occupancy, city |
attractions/attractions.csv |
Name, Latitude, Longitude, Address, Phone, Website, City |
googleDistanceMatrix/distance.csv |
origin, destination, cost, duration, distance |
Common grep patterns
Find cities in a state
grep -i "ohio" data/background/citySet_with_states.txt
# → Toledo, Cleveland, Dayton, Columbus, Akron, Cincinnati
Find distances between two cities
grep -i "^Minneapolis," data/googleDistanceMatrix/distance.csv | grep -i "Cleveland"
# → Minneapolis,Cleveland,,11 hours 14 mins,1219 km
Find pet-friendly accommodations in a city
# "No pets" in house_rules = NOT pet-friendly; absence = pet-friendly
grep -i ",Cleveland$" data/accommodations/clean_accommodations_2022.csv | grep -v "No pets"
Filter by min occupancy
# column 8 (0-indexed) = maximum_occupancy
grep -i ",Columbus$" data/accommodations/clean_accommodations_2022.csv \
| grep -v "No pets" \
| awk -F',' '$8 >= 2'
Find restaurants by cuisine and city
grep -i ",Cleveland," data/restaurants/clean_restaurant_2022.csv \
| grep -i "american\|mediterranean\|chinese\|italian"
Find attractions in a city
grep -i ",Cleveland$" data/attractions/attractions.csv | cut -d',' -f1
Budget calculation approach
- Accommodation:
price × number_of_nights; respectminimum nights. - Meals:
Average Costin the restaurant CSV is the estimated cost for the meal. - No flights means all travel is self-driving; use the
distance.csvfor durations.
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.
- 5d ago First seen · 66 lines · 31 tokens per session scan A e6604c304663
travel-itinerary-data is a skill published in the GitHub repository cxcscmu/SkillLearnBench (83 stars, last pushed 2mo ago), licensed MIT. It adds 31 tokens to every session and 682 once invoked, about $0.0002 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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