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 agentmods add skills/stringhost/gemma-skills/restaurant-roulettenpx skills add StrinGhost/gemma-skills --skill restaurant-roulettegit clone --depth 1 https://github.com/StrinGhost/gemma-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/stringhost/gemma-skills/restaurant-roulette)<a href="https://agentmods.dev/skills/stringhost/gemma-skills/restaurant-roulette"><img src="https://agentmods.dev/badge/skills/stringhost/gemma-skills/restaurant-roulette.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 | $0.00022 | $0.00293 |
| Opus 5 | $0.00011 | $0.00147 |
| Sonnet 5 | $0.00004 | $0.00059 |
| Haiku 4.5 | $0.00002 | $0.00029 |
Grade A, and why
restaurant-roulette 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 6d 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
Restaurant Roulette
This skill searches for up to 10 restaurants matching a specific cuisine and location in a spin wheel.
Examples
- "Suggest Mexican food in San Jose."
- "Find a random Italian restaurant near Sunnyvale."
- "Where should I get Sushi in San Francisco today?"
- "Show a restaurant roulette for Indian food in Palo Alto."
Instructions
Call the run_js tool with the following exact parameters:
- data: A JSON string with the following fields
- location: the target city or location (e.g., "San Jose", "Sunnyvale", "San Francisco").
- cuisine: the style of food or cuisine desired (e.g., "Mexican", "Italian", "Indian", "Sushi").
DO NOT use any other tool, DO NOT call run_intent.
IMPORTANT: When the wheel is generated, DO NOT pick a winner for the user or make up a restaurant. Simply return the requested webview and tell the user to tap the preview card to spin the wheel themselves.
What ships with it
5 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.
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.
- 6d ago First seen · 30 lines · 22 tokens per session scan A 9bd023006d41
restaurant-roulette is a skill published in the GitHub repository StrinGhost/gemma-skills (54 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 22 tokens to every session and 293 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 2026-08-30.
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