Borrowing it
Nothing to install: this file belongs to lxinfei5/research-os. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/lxinfei5/research-os/main/.agents/skills/researchos-travel/SKILL.mdgit clone --depth 1 https://github.com/lxinfei5/research-osWrote 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/lxinfei5/research-os/researchos-travel)<a href="https://agentmods.dev/skills/lxinfei5/research-os/researchos-travel"><img src="https://agentmods.dev/badge/skills/lxinfei5/research-os/researchos-travel/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/lxinfei5/research-os/researchos-travel"><img src="https://agentmods.dev/badge/skills/lxinfei5/research-os/researchos-travel.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 | $0.00305 |
| Opus 5 | $0.00020 | $0.00152 |
| Sonnet 5 | $0.00008 | $0.00061 |
| Haiku 4.5 | $0.00004 | $0.00030 |
Grade A, and why
researchos-travel 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 13d 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
ResearchOS · Travel (example domain)
Full rationale: pillars/examples/travel.md.
When
User wants a trip plan / weekend drive / “where to eat and stay” that needs live multi-source checks.
Method
- Purpose — one sentence (rest / kids / budget / photos).
- Main contradiction — e.g. drive time vs quiet.
- Discover — multi-source on channels you trust (maps, booking, review apps, …; ≥2 independent for each key pick).
- Corroborate — 2 of {official listing, recent multi-app reviews, dated photo/menu}.
- Emit — user surface first (
pillars/output/THESIS.md): go/don’t + where to sleep + one flip. Day blocks only if they are the act. 2-of-3 tags, backups, hours, sources stay on the audit surface.
Optional HTML skin: template.html (map-friendly). Prefer the act over chrome.
Do not
- Optimize anti-bot playbooks here
- Rank “best city ever” without evidence classes
- Invent opening hours
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 13d ago First seen · 32 lines · 41 tokens per session scan A 709e76d39204
researchos-travel is a skill published in the GitHub repository lxinfei5/research-os (97 stars, last pushed 13d ago), licensed MIT. It adds 41 tokens to every session and 305 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 2026-08-30.
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