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 zubair-trabzada/ai-restaurant-claude --skill restaurant-menugit clone --depth 1 https://github.com/zubair-trabzada/ai-restaurant-claudeWrote 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/zubair-trabzada/ai-restaurant-claude/restaurant-menu)<a href="https://agentmods.dev/skills/zubair-trabzada/ai-restaurant-claude/restaurant-menu"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-restaurant-claude/restaurant-menu/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/zubair-trabzada/ai-restaurant-claude/restaurant-menu"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-restaurant-claude/restaurant-menu.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 | $0.00038 | $0.02658 |
| Opus 5.5 | $0.00015 | $0.01063 |
| Sonnet 5.5 | $0.00008 | $0.00532 |
| Haiku 4.5 | $0.00004 | $0.00266 |
Grade A, and why
restaurant-menu 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.
How it starts
The opening of the file, as written. The whole thing — 284 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Menu Engineering Analysis
You analyze a restaurant menu using the Kasavana & Smith menu engineering framework, scoring each item on popularity and contribution margin, then producing concrete recommendations to lift average check size and overall menu profitability.
DISCLAIMER: AI-generated menu analysis based on publicly available menu data and industry benchmarks. The restaurant owner should verify item-level cost and sales data.
When to use
/restaurant menu <name-or-url>— full menu engineering audit- "menu analysis for [name]"
- "what should I change about my menu"
The Kasavana & Smith Matrix
Every menu item plots on a 2x2 grid:
| High Margin | Low Margin | |
|---|---|---|
| High Popularity | STARS — protect, feature | PLOWHORSES — re-engineer cost or raise price |
| Low Popularity | PUZZLES — re-merchandise or relocate on menu | DOGS — remove |
Definitions:
- Margin = menu price - food cost
- Popularity = % of category orders > category mean
Execution Pipeline
Step 1: Acquire Menu
Sources in priority order:
- Restaurant website (most accurate)
- Google Business Profile menu
- Yelp menu
- Third-party (Uber Eats, DoorDash) — note prices may include markup
- Photos of physical menu
WebSearch("[name] [city] menu prices")
WebSearch("[name] [city] menu pdf")
Step 2: Catalog Every Item
For each item capture:
- Category (appetizer / entrée / side / dessert / drink)
- Name
- Description (full text)
- Price
- Photo present Y/N
- Position in category (1st, 2nd, 3rd, etc.)
- Any descriptors (chef's special, popular, gluten-free, signature)
- Estimated food cost % (use industry standards if actual unknown):
- Pasta dishes: 18-25%
- Steaks/seafood: 30-40%
- Burgers/sandwiches: 25-32%
- Pizza: 20-30%
- Appetizers: 20-30%
- Desserts: 15-25%
- Cocktails: 18-22%
- Wine: 25-35%
Step 3: Apply Kasavana Matrix
For each item, estimate:
- Contribution margin = price - (price × est. food cost %)
- Popularity = best guess based on menu position, descriptors, photo presence, review mentions
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 · 284 lines · 38 tokens per session scan A 4ca47a3a6a4a
restaurant-menu is a skill published in the GitHub repository zubair-trabzada/ai-restaurant-claude (34 stars, last pushed 5mo ago), licensed MIT. It adds 38 tokens to every session and 2,658 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
add-community-extension
Add a community extension to the Spec Kit catalog from a GitHub issue submission. USE FOR: processing extension submission issues, validating catalog entries, updating catalog.community.json and docs/community/extensions.md, creating PRs. DO NOT USE FOR: creating new extensions from scratch, or first-party extension…
openspec-explore
Enter OpenSpec explore mode - a thinking partner for exploring ideas, investigating problems, and clarifying requirements in a project that uses OpenSpec. Use when the user wants to think through something before or during an OpenSpec change. Also use when the user says "openspec explore" or "opsx explore".
openspec-verify-change
Verify implementation matches OpenSpec change artifacts. Use when the user wants to validate that implementation is complete, correct, and coherent before archiving. Also use when the user says "openspec verify" or "opsx verify".
openspec-apply-change
Implement tasks from an OpenSpec change. Use when the user wants to start implementing, continue implementation, or work through tasks. Also use when the user says "openspec apply", "opsx apply", or "openspec implement".
openspec-update-change
Update an OpenSpec change by revising its existing planning artifacts and keeping them coherent with one another. Use when the user wants to revise a change's plan, fold new decisions into it, or reconcile its artifacts after an edit. Also use when the user says "openspec update change" or "opsx update". If the user…
openspec-new-change
Start a new OpenSpec change using the experimental artifact workflow. Use when the user wants to create a new feature, fix, or modification with a structured step-by-step approach. Also use when the user says "openspec new change" or "opsx new".