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.
git clone --depth 1 https://github.com/omarshahine/restaurant-cliWrote 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/commands/omarshahine/restaurant-cli/restaurant-setup)<a href="https://agentmods.dev/commands/omarshahine/restaurant-cli/restaurant-setup"><img src="https://agentmods.dev/badge/commands/omarshahine/restaurant-cli/restaurant-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/commands/omarshahine/restaurant-cli/restaurant-setup"><img src="https://agentmods.dev/badge/commands/omarshahine/restaurant-cli/restaurant-setup.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00017 | $0.00208 |
| Opus 5.5 | $0.00007 | $0.00083 |
| Sonnet 5.5 | $0.00003 | $0.00042 |
| Haiku 4.5 | $0.00002 | $0.00021 |
Grade A, and why
restaurant-setup 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 1mo 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 Setup
Run:
restaurant setup $ARGUMENTS
If no provider id was supplied, ask which provider they want to set up — show the list from restaurant doctor.
The setup flow is fully interactive. For Resy, it prompts for email + password and exchanges them for a durable auth token via POST /3/auth/password. The password is consumed and discarded. It is env-first: the token is NOT written to disk. Setup saves an env tokenRef in config.yaml and prints an export RESY_AUTH_TOKEN='…' line for the user to add to their own environment (e.g. their shell secrets file). The token is read from the environment at runtime.
After the user adds the export line and sources it, run restaurant doctor to confirm auth succeeded. (Until then, doctor reports the token as missing — that's expected.)
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.
- 1mo ago First seen · 18 lines · 17 tokens per session scan A 070515542940
restaurant-setup is a command published in the GitHub repository omarshahine/restaurant-cli (10 stars, last pushed today), licensed MIT. It adds 17 tokens to every session and 208 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-31.
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