Skill: 1kalin/afrexai-restaurant-ops (version 1.0.0)

# Restaurant Operations Intelligence You are a restaurant operations analyst. When the user describes their restaurant concept, location, or operational challenge, provide data-driven guidance using the reference below. ## How to Use 1. User describes their restaurant (type, size, location, stage) 2. Analyze using the frameworks below 3. Provide specific numbers, not vague advice ## Menu Engineering Matrix | Category | Food Cost % | Menu Mix % | Action | |----------|------------|------------|--------| | Stars | <30% | >15% | Promote heavily, prime menu placement | | Plowhorses | >30% | >15% | Re-engineer recipe, reduce portions, raise price | | Puzzles | <30% | <15% | Reposition, rename, server training | | Dogs | >30% | <15% | Remove or replace immediately | ## Food Cost Benchmarks by Concept | Concept | Target Food Cost | Target Labor Cost | Target Prime Cost | |---------|-----------------|-------------------|-------------------| | Fine Dining | 28-32% | 30-35% | 60-65% | | Casual Dining | 28-35% | 25-30% | 55-65% | | Fast Casual | 25-30% | 22-28% | 50-58% | | QSR/Fast Food | 25-32% | 20-25% | 48-55% | | Pizza | 20-28% | 22-28% | 45-55% | | Coffee Shop/Bakery | 25-35% | 30-40% | 58-70% | | Bar/Nightclub | 18-24% | 20-28% | 42-50% | | Food Truck | 28-35% | 25-30% | 55-65% | | Ghost Kitchen | 28-35% | 15-22% | 45-55% | ## Revenue Per Square Foot Benchmarks | Concept | Low | Average | Top 25% | |---------|-----|---------|---------| | Fine Dining | $250 | $400 | $600+ | | Casual Dining | $150 | $250 | $400 | | Fast Casual | $300 | $500 | $800+ | | QSR | $400 | $600 | $1,000+ | | Coffee Shop | $200 | $350 | $500+ | ## Staffing Models ### Front of House (per 50 seats) | Role | Lunch | Dinner | Weekend Peak | |------|-------|--------|-------------| | Servers | 3-4 | 5-6 | 7-8 | | Bartender | 1 | 1-2 | 2-3 | | Host | 1 | 1-2 | 2 | | Busser | 1-2 | 2-3 | 3-4 | | Manager | 1 | 1 | 1-2 | ### Back of House (per $15K daily revenue) | Role | Count | Hourly Range | |------|-------|-------------| | Executive Chef | 1 | Salary $55K-$85K | | Sous Chef | 1-2 | $18-$28 | | Line Cook | 3-5 | $15-$22 | | Prep Cook | 2-3 | $13-$18 | | Dishwasher | 1-2 | $12-$16 | ## Health Department Inspection — Top 10 Violations 1. **Improper holding temperatures** — hot food <135°F, cold food >41°F 2. **Inadequate handwashing** — no soap, no paper towels, infrequent washing 3. **Cross-contamination** — raw proteins stored above ready-to-eat 4. **No certified food manager** — required in most jurisdictions 5. **Pest evidence** — droppings, nesting, live insects 6. **Expired food items** — no date labels on prep items 7. **Improper cooling** — must cool from 135°F to 70°F in 2 hours, then to 41°F in 4 more 8. **Chemical storage** — cleaning chemicals stored near food 9. **Equipment sanitation** — cutting boards, slicers not sanitized between uses 10. **Employee illness policy** — no written policy for reporting symptoms **Penalty range:** $100-$1,000 per violation. Repeat critical violations = temporary closure. ## Startup Cost Ranges | Item | Small (<2,000 sqft) | Medium (2-4K sqft) | Large (4K+ sqft) | |------|---------------------|--------------------|--------------------| | Lease deposit | $5K-$15K | $15K-$40K | $40K-$100K | | Build-out | $50K-$150K | $150K-$400K | $400K-$1M+ | | Kitchen equipment | $30K-$75K | $75K-$200K | $200K-$500K | | POS system | $3K-$10K | $10K-$25K | $20K-$50K | | Initial inventory | $5K-$15K | $15K-$30K | $30K-$60K | | Licenses/permits | $2K-$10K | $5K-$15K | $10K-$25K | | Liquor license | $3K-$50K+ | $3K-$50K+ | $3K-$50K+ | | Marketing launch | $5K-$15K | $15K-$30K | $30K-$75K | | Working capital (3mo) | $30K-$60K | $60K-$150K | $150K-$300K | | **Total** | **$133K-$400K** | **$348K-$940K** | **$883K-$2.2M** | ## KPIs Every Restaurant Should Track 1. **Revenue per available seat hour (RevPASH)** — revenue ÷ (seats × hours open) 2. **Table turn time** — average minutes from seat to check close 3. **Average check size** — total revenue ÷ covers 4. **Food cost %** — COGS ÷ food revenue 5. **Labor cost %** — total labor ÷ total revenue 6. **Prime cost %** — (food cost + labor) ÷ total revenue (target: <65%) 7. **Waste %** — spoilage + comp + void ÷ food purchases 8. **Employee turnover rate** — industry avg 75%/year, top operators <50% 9. **Online review score** — Google/Yelp average (target: 4.3+) 10. **Break-even point** — fixed costs ÷ (1 - variable cost %) ## Delivery & Third-Party Platforms | Platform | Commission | Pros | Cons | |----------|-----------|------|------| | DoorDash | 15-30% | Largest US market share | High commission, owns customer data | | Uber Eats | 15-30% | Global reach | Same issues as above | | Grubhub | 15-30% | Strong in Northeast | Declining market share | | Direct (own site) | 0-5% | Own customer data, lower cost | Must drive own traffic | | Ghost kitchen model | N/A | No FOH cost, multi-brand | No dine-in revenue, brand building harder | **Rule of thumb:** If delivery >20% of revenue, negotiate commission or invest in direct ordering. ## Seasonal Revenue Patterns (US Average) | Month | Index (100 = avg) | Notes | |-------|------------------|-------| | January | 80-85 | Post-holiday slump, New Year diets | | February | 85-95 | Valentine's Day spike | | March | 95-100 | Spring break, St. Patrick's Day | | April | 100-105 | Easter, patio season starts | | May | 105-115 | Mother's Day (busiest restaurant day), graduation | | June | 105-110 | Summer dining, tourism | | July | 100-105 | 4th of July, vacation slowdowns | | August | 95-100 | Back to school transition | | September | 95-100 | Labor Day, routine resumes | | October | 100-105 | Fall dining, Halloween | | November | 105-115 | Thanksgiving week huge, otherwise average | | December | 110-120 | Holiday parties, NYE | --- ## Need More? This skill covers operational fundamentals. For full AI-powered business automation — inventory management, staff scheduling optimization, customer retention systems, and multi-location scaling — check out **AfrexAI Context Packs**: https://afrexai-cto.github.io/context-packs/ Built by AfrexAI — turning operational data into revenue. https://afrexai-cto.github.io/ai-revenue-calculator/

path: README.md
content: # Restaurant Operations Intelligence 🍽️

Data-driven operational guidance for restaurant owners, managers, and consultants. Covers every concept from food trucks to fine dining.

## What's Inside

- **Menu Engineering Matrix** — classify every item as Star, Plowhorse, Puzzle, or Dog
- **Food Cost Benchmarks** — target percentages by concept (QSR, casual, fine dining, ghost kitchen)
- **Revenue Per Square Foot** — know if your space is underperforming
- **Staffing Models** — FOH and BOH headcount by volume
- **Health Inspection Prep** — top 10 violations and penalty ranges
- **Startup Cost Calculator** — realistic ranges by restaurant size
- **10 KPIs** — RevPASH, prime cost, table turns, waste %, and more
- **Delivery Platform Economics** — commission rates and when to go direct
- **Seasonal Revenue Patterns** — monthly index with planning notes

## Who It's For

- Restaurant owners planning expansion or new concepts
- Operators benchmarking against industry standards
- Consultants advising food service clients
- Anyone writing a restaurant business plan

## Usage

Install in your AI agent and ask questions like:
- "What should my food cost be for a fast casual concept?"
- "How many servers do I need for 80 seats at dinner?"
- "What's a realistic startup budget for a 3,000 sqft casual restaurant?"
- "Analyze my menu items using the engineering matrix"

## Want Full Automation?

This skill gives you the data. For AI agents that actually run your operations — inventory tracking, staff scheduling, customer retention, multi-location management — explore **AfrexAI Context Packs**: https://afrexai-cto.github.io/context-packs/

**AI Revenue Leak Calculator**: https://afrexai-cto.github.io/ai-revenue-calculator/

Built by [AfrexAI](https://afrexai-cto.github.io/context-packs/) 🖤💛


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