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 pet-friendly-filteringgit 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/pet-friendly-filtering)<a href="https://agentmods.dev/skills/cxcscmu/skilllearnbench/pet-friendly-filtering"><img src="https://agentmods.dev/badge/skills/cxcscmu/skilllearnbench/pet-friendly-filtering.svg" alt="Measured on agentmods" 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 | $0.00020 | $0.00226 |
| Opus 5 | $0.00010 | $0.00113 |
| Sonnet 5 | $0.00004 | $0.00045 |
| Haiku 4.5 | $0.00002 | $0.00023 |
Grade A, and why
pet-friendly-filtering 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
Pet-Friendly Accommodation Filtering
How It Works
The house_rules column in clean_accommodations_2022.csv contains rules separated by " & ".
Common rules: "No pets", "No smoking", "No parties", "No children under 10", "No visitors".
Filtering Logic
- Pet-friendly: Any accommodation where
house_rulesdoes NOT contain "No pets" - An empty
house_rulesfield means no restrictions — pets are allowed - Rules like "No smoking" or "No parties" do NOT exclude pets
Command
grep -i "cityname" data/accommodations/clean_accommodations_2022.csv | grep -iv "no pets"
Additional Checks
- Verify
maximum occupancy >= number of travelers - Verify
minimum nights <= planned stay length - Consider
room type: "Entire home/apt" is generally better for pets than "Shared room"
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 · 26 lines · 20 tokens per session scan A 15d691a71f68
pet-friendly-filtering is a skill published in the GitHub repository cxcscmu/SkillLearnBench (83 stars, last pushed 1mo ago), licensed MIT. It adds 20 tokens to every session and 226 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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