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 naveedharri/benai-skills --skill rented-server-setupgit clone --depth 1 https://github.com/naveedharri/benai-skillsWrote 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/naveedharri/benai-skills/rented-server-setup)<a href="https://agentmods.dev/skills/naveedharri/benai-skills/rented-server-setup"><img src="https://agentmods.dev/badge/skills/naveedharri/benai-skills/rented-server-setup/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/naveedharri/benai-skills/rented-server-setup"><img src="https://agentmods.dev/badge/skills/naveedharri/benai-skills/rented-server-setup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 132 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00258 | $0.04798 |
| Opus 5 | $0.00129 | $0.02399 |
| Sonnet 5 | $0.00052 | $0.00960 |
| Haiku 4.5 | $0.00026 | $0.00480 |
Grade A, and why
rented-server-setup 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 7d 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.
- **OVH**: https://www.ovh.com/manager/ (redirects to their regional manager) → Public Cloud → AI & Machine Learning → AI Endpoints → API keys. The keyless trial at 2 requests/min can prove the route before they create a How it starts
The opening of the file, as written. The whole thing — 218 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rented Server Setup
The cloud counterpart to scan-my-machine. That skill tells someone what their laptop can run. This one runs what it cannot, and it carries two builds because "run a big model in the cloud" has two honest answers depending on usage shape and what "private" means:
- Route A, the EU endpoint. OVHcloud AI Endpoints: a per-token OpenAI-compatible API run by a French company in Gravelines, France. Cents per million tokens, zero idle cost solo. Two shapes: solo, where each user's own app points at the endpoint, and team, where one shared Open WebUI runs on a small OVH VPS for about €5 a month. Multi-tenant either way.
- Route B, the private pod. One RunPod Secure Cloud pod in a region the user picks, two locked doors: Open WebUI behind its login for the team, vLLM's API behind a generated key for Claude Code and other apps. Single-tenant, any model with a vLLM recipe, one shared URL for a team. Bills every hour it exists, used or not.
The order is: questions first, then two named recommendations with prices computed from the answers, then the user picks a provider and everything after is yours: token, wire, prove, report. Beyond creating their own credential they should not have to open a dashboard, paste a URL, or copy an endpoint ID.
Two things are never automatic. The spend, in references/cost-gate.md. And on Route B the region, which the user chooses and you never default.
1. Before you start
Run the check in references/environment-check.md. It is deliberately short: nothing here runs on the user's machine, so do not scan their hardware and do not report on it.
If a local model would do the job, they should be in local-ai-setup instead. Say that in one line and move on.
2. The questions
One AskUserQuestion, three questions, no provider named yet. Full option text in references/model-picker.md section 0.
- What should the model be best at. Show the categories from the open-model leaderboard at https://onyx.app/open-llm-leaderboard — overall, coding, math, chat, reasoning — plus a "name a specific model" option. The recommended default is Qwen3.6-27B: A-tier overall at only 27B, cheap on both providers. Verify whatever they pick live: the OVH catalog (
ovh-endpoints.mdsection 2) for Route A,model-sources.mdfor Route B. - Who will use it. Solo, or a team on one shared URL.
- Usage rhythm. Spiky and on-and-off, or heavy and sustained. This decides the whole cost story, which is why it is asked before any price is shown.
What ships with it
11 files 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.
- references/cost-gate.md 8.1 KB
- references/deploy-steps.md 30 KB
- references/environment-check.md 3.8 KB
- references/model-picker.md 12 KB
- references/model-sources.md 9.2 KB
- references/ovh-endpoints.md 7.8 KB
- references/ovh-team-interface.md 4.2 KB
- references/report-template.md 18 KB
- references/teardown.md 6.2 KB
- references/troubleshooting.md 16 KB
- references/trust-boundary.md 14 KB
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.
- 7d ago First seen · 218 lines · 258 tokens per session scan A d1c89e158f2c
rented-server-setup is a skill published in the GitHub repository naveedharri/benai-skills (61 stars, last pushed today), licensed MIT. It adds 258 tokens to every session and 4,798 once invoked, about $0.0013 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 2026-09-05.
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