Agent Native

restaurant-menu

This skill analyzes restaurant menus using the Kasavana & Smith framework, classifying each item as a Star, Plowhorse, Puzzle, or Dog based on popularity and…

by zubair-trabzadaCommunityNot reviewed

Community author

Agents
Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode
License
MIT (permissive)
Pin
fb42fb7pinned Oct 9, 2026
Context cost
about 2,500 tokenswhen the skill loads
GitHub stars
31on zubair-trabzada/ai-restaurant-claude
Scripts
None found

What it does

“Menu engineering analysis — item placement, description quality, pricing psychology, upsell opportunities, photo presence, Kasavana matrix (Stars/Plowhorses/Puzzles/Dogs)”
The author's description, from SKILL.md

Generated summary from the skill's own text

This skill analyzes restaurant menus using the Kasavana & Smith framework, classifying each item as a Star, Plowhorse, Puzzle, or Dog based on popularity and profit margin. It evaluates menu structure, description quality, pricing psychology, photos, and upsell opportunities, then produces a detailed report with five high-impact recommendations to increase average check size and profitability.

When to use it

  • Restaurant owners optimizing menu profitability and layout
  • Analyzing pricing strategy and description effectiveness
  • Identifying which menu items to promote, reprice, or remove
  • Planning menu redesigns or photo shoots

When not to

  • When actual item-level cost and sales data are unavailable
  • For menus with fewer than 10 items or highly seasonal offerings
  • When a simpler menu review without detailed matrix analysis is needed

Install

These commands install from the publisher's repository and need no account.

skills CLI

npx skills add zubair-trabzada/ai-restaurant-claude --skill restaurant-menu

Installs from the repository's default branch, which may have changed since the commit we checked.

GitHub CLI 2.90 or later

gh skill install zubair-trabzada/ai-restaurant-claude restaurant-menu@fb42fb709be4fe1d1519d53392d1bad69d8a4965

Installs the commit we checked (fb42fb7).

Copy by hand

Download the folder at fb42fb7 and put it in .claude/skills/restaurant-menu for Claude Code and in .agents/skills/restaurant-menu for Codex, Cursor, Gemini CLI, GitHub Copilot and OpenCode.

Skill folder on GitHub at fb42fb7

Copy for your agent

A prompt for any coding agent. It installs this skill from GitHub at the pinned commit, copies the files as they are, and runs nothing unless you ask.

Prompt

Install the agent skill "restaurant-menu" by zubair-trabzada.

Source, pinned to commit fb42fb709be4fe1d1519d53392d1bad69d8a4965:
https://github.com/zubair-trabzada/ai-restaurant-claude/tree/fb42fb709be4fe1d1519d53392d1bad69d8a4965/skills/restaurant-menu

1. Download that folder at exactly this commit. Do not use the default branch.
2. Copy every file unchanged, keeping the folder structure, into .claude/skills/restaurant-menu/ for Claude Code and .agents/skills/restaurant-menu/ for Codex, Cursor, Gemini CLI, GitHub Copilot and OpenCode. Create the folders if they do not exist.
3. Do not edit the files, and do not run any script in the folder unless I ask you to.
4. When you are done, list the files you copied and where you put them.

Listing and checks: https://www.agentnative.dev/skills/zubair-trabzada/restaurant-menu

SKILL.md at the pin

---
name: restaurant-menu
description: Menu engineering analysis — item placement, description quality, pricing psychology, upsell opportunities, photo presence, Kasavana matrix (Stars/Plowhorses/Puzzles/Dogs)
version: 1.0.0
author: AI Restaurant Team
tags: [restaurant, menu, engineering, kasavana, pricing]
command: /restaurant menu <url-or-name>
output: RESTAURANT-MENU-[Name].md
---

# 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:
1. Restaurant website (most accurate)
2. Google Business Profile menu
3. Yelp menu
4. Third-party (Uber Eats, DoorDash) — note prices may include markup
5. 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

Plot each item as Star / Plowhorse / Puzzle / Dog.

### Step 4: Score 5 Sub-Dimensions

| Dimension | What to Check | Score (0-20) |
|-----------|---------------|--------------|
| Menu Structure & Layout | Categories logical? Length appropriate? Star placement in golden triangle? | ... |
| Description Quality | Sensory language, origin stories, ingredient highlights, length 15-30 words? | ... |
| Pricing Psychology | Charm pricing ($14.95 vs $15)? Decoy items? Anchoring (high-price first)? Currency symbols dropped? | ... |
| Photo Presence | Photos for high-margin items? Quality? Consistency? | ... |
| Upsell / Combo Engineering | Add-ons, combos, dessert nudges, drink pairings, sides upgrades? | ... |

### Step 5: Identify Quick Wins

The 5 highest-leverage menu changes:
1. Reposition Stars to the golden triangle (top-right, top-left, first item in category)
2. Rewrite descriptions for Plowhorses to boost margin perception
3. Re-merchandise Puzzles with photos and "chef's pick" badges
4. Remove or replace Dogs (free up real estate)
5. Add 2-3 strategic combos / add-ons for 8-12% ticket lift

---

## Pricing Psychology Reference

| Tactic | When to use | Example |
|--------|-------------|---------|
| Charm pricing (.95, .99) | Casual / value-driven concepts | $14.95 vs $15.00 |
| Round pricing (whole dollars) | Premium / fine dining | "32" vs "$32.00" |
| Drop currency symbols | Removes "spending" psychology | "Burger 16" |
| Decoy effect | Anchor a premium item to make others look reasonable | $48 ribeye makes $32 strip steak feel cheap |
| Bracket pricing | 3 price tiers per category (low/mid/high) — mid sells most | $12 / $18 / $26 |
| Avoid price columns | Right-aligned price columns invite price comparison | Inline price after description |
| Avoid dollar signs | Especially in fine dining | $14 → 14 |

---

## Description Quality Rubric

A great menu description (15-30 words):

✅ Uses sensory language (crispy, slow-braised, hand-rolled, charred)
✅ Names 2-3 key ingredients
✅ Mentions origin or technique (Sicilian, wood-fired, 36-month aged)
✅ Hints at preparation (chef's signature, family recipe)
✅ Differentiates from competitors

❌ Generic ("delicious chicken with vegetables")
❌ Just a list of components
❌ Over 40 words (decision fatigue)
❌ Under 8 words for items > $20 (feels cheap)

---

## Golden Triangle / Eye Tracking

Eye-tracking studies show diners read menus in this pattern:

```
1. Top-right corner  ← place 2 highest-margin items here
2. Top-left corner   ← place signature / story-driven items here
3. Center            ← middle ground
4. Bottom-left
5. Bottom-right      ← place items you want LESS attention on
```

Within categories: first item gets 20% more attention. Last item gets 15% more attention. Middle items get the least.

---

## Output Template

Save to `RESTAURANT-MENU-[Name].md`:

```markdown
# Menu Engineering Analysis: [NAME]

> **Generated:** [DATE] | **Menu Score:** [X]/100 | **Total Items Analyzed:** [N]

**DISCLAIMER: AI-generated menu analysis. Verify item-level cost data with the owner.**

## Menu Health Snapshot

| Metric | Value | Industry Benchmark |
|--------|-------|---------------------|
| Total items | X | 20-30 (sweet spot) |
| Avg item price | $X.XX | ... |
| Items with photos | X% | 30-50% (digital), 0-20% (print) |
| Avg description length | X words | 15-30 words |
| Estimated avg food cost | X% | 28-32% |
| Pricing strategy | [Charm / Round / Mixed] | ... |

## Kasavana Matrix Distribution

| Quadrant | Item Count | % of Menu |
|----------|------------|-----------|
| Stars (high pop, high margin) | X | X% |
| Plowhorses (high pop, low margin) | X | X% |
| Puzzles (low pop, high margin) | X | X% |
| Dogs (low pop, low margin) | X | X% |

## Item-by-Item Analysis

### Entrées

| Item | Price | Est. Margin | Pop. | Classification | Recommendation |
|------|-------|-------------|------|----------------|----------------|
| Spaghetti Carbonara | $19 | $14.25 | High | Star | Move to top-right of menu; add chef story |
| Lasagna | $17 | $11.50 | High | Plowhorse | Raise to $18.50 (price elasticity weak here) |
| Branzino | $32 | $22.40 | Low | Puzzle | Add photo, badge "Chef's Pick" |
| Caesar Salad Entrée | $14 | $9.80 | Low | Dog | Remove or convert to half-portion side |

### Appetizers, Sides, Desserts
[same table structure]

## 5 Quick-Win Recommendations

### 1. Reposition Stars to the Golden Triangle
- Move Spaghetti Carbonara to top-right position
- Move Margherita Pizza (signature) to top-left
- Expected impact: +5-8% category sales lift

### 2. Rewrite Plowhorse Descriptions
- Current Lasagna description: "Traditional lasagna with meat sauce." (8 words)
- Suggested: "Hand-layered with Bolognese braised 6 hours, fresh ricotta, and Grana Padano — Nonna Maria's recipe since 1962." (20 words)
- Expected impact: support price increase from $17 → $18.50 without complaints

### 3. Re-Merchandise Puzzles
- Branzino — add photo + "Chef's Pick" badge
- Veal Saltimbocca — pair with house Chianti as a "Tuscany Tasting"
- Expected impact: 30-50% lift in low-pop high-margin item sales

### 4. Remove or Convert Dogs
- Caesar Salad Entrée — remove (low margin, cannibalizes appetizer Caesar)
- Three Cheese Ravioli — replace with seasonal special slot
- Expected impact: freed menu real estate + lower waste

### 5. Add 3 Strategic Add-ons
- "Make it a Bolognese" — add ground beef to any pasta for $4 (90%+ margin)
- "Truffle upgrade" — shaved truffle on any pasta for $7
- "Tiramisu duo" — small tasting + espresso for $8
- Expected ticket lift: +$3.50/cover = +$X,XXX/month at current covers

## Pricing Psychology Audit

| Element | Current State | Recommendation |
|---------|---------------|----------------|
| Charm vs round pricing | Mixed | Standardize on round (concept is mid-premium) |
| Currency symbols | Used | Drop "$" — less price-focus |
| Price alignment | Right-aligned column | Move to inline at end of description |
| Decoy item | None | Add $42 Ribeye to anchor entrée prices down |

## Photo Audit

| Item | Has Photo? | Should It? |
|------|------------|------------|
| Carbonara (Star) | Yes | Yes — keep |
| Branzino (Puzzle) | No | YES — add immediately |
| Lasagna (Plowhorse) | Yes | Yes — but quality is poor, reshoot |
| Caesar (Dog) | No | No — being removed |

## Menu Score Breakdown

| Dimension | Score | Notes |
|-----------|-------|-------|
| Structure & Layout | X/20 | ... |
| Description Quality | X/20 | ... |
| Pricing Psychology | X/20 | ... |
| Photo Presence | X/20 | ... |
| Upsell / Combo Engineering | X/20 | ... |
| **Total** | **X/100** | |

## Revenue Impact Projection

If the 5 quick wins are implemented:
- Avg check size lift: +$2.80 (8.5%)
- At [N] daily covers × 30 days: **+$X,XXX/month revenue lift**
- No change in food cost % expected

## What to Implement First

1. **This week:** Move Stars to golden triangle (zero cost, just menu redesign)
2. **This week:** Add 3 strategic add-ons (zero food cost change)
3. **Within 2 weeks:** Rewrite Plowhorse descriptions, raise prices
4. **Within 30 days:** Reshoot photos for Puzzles + signature items
5. **Within 60 days:** Full menu reprint with all changes

**DISCLAIMER: AI-generated analysis. Always verify item-level food cost and sales mix data with the owner before raising prices or removing items.**
```

---

## Quality Standards

- Every item gets a classification (no skipping)
- Every recommendation includes a revenue impact estimate
- Pricing recommendations consider local competition and concept tier
- Photo recommendations factor in cost ($500-$2,000 for a 20-item shoot)

**DISCLAIMER: For educational/research purposes only. AI-generated.**

From zubair-trabzada/ai-restaurant-claude at fb42fb7, shown as plain text under its license: MIT (permissive). The license text is in LICENSE.

View SKILL.md on GitHub at fb42fb7

Files

1 file, 10 KB in total. Each file has a sha256 in the pin's manifest; the first 12 characters are shown.

Skill folder on GitHub at fb42fb7
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