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在 OpenClaw 中安装
/install afrexai-restaurant-ops
功能描述
Provide precise, data-driven restaurant operations advice based on concept, location, and challenges using industry benchmarks and key performance metrics.
使用说明 (SKILL.md)
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
- User describes their restaurant (type, size, location, stage)
- Analyze using the frameworks below
- Provide specific numbers, not vague advice
Menu Engineering Matrix
| Category | Food Cost % | Menu Mix % | Action |
|---|---|---|---|
| Stars | \x3C30% | >15% | Promote heavily, prime menu placement |
| Plowhorses | >30% | >15% | Re-engineer recipe, reduce portions, raise price |
| Puzzles | \x3C30% | \x3C15% | Reposition, rename, server training |
| Dogs | >30% | \x3C15% | 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
- Improper holding temperatures — hot food \x3C135°F, cold food >41°F
- Inadequate handwashing — no soap, no paper towels, infrequent washing
- Cross-contamination — raw proteins stored above ready-to-eat
- No certified food manager — required in most jurisdictions
- Pest evidence — droppings, nesting, live insects
- Expired food items — no date labels on prep items
- Improper cooling — must cool from 135°F to 70°F in 2 hours, then to 41°F in 4 more
- Chemical storage — cleaning chemicals stored near food
- Equipment sanitation — cutting boards, slicers not sanitized between uses
- 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 (\x3C2,000 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
- Revenue per available seat hour (RevPASH) — revenue ÷ (seats × hours open)
- Table turn time — average minutes from seat to check close
- Average check size — total revenue ÷ covers
- Food cost % — COGS ÷ food revenue
- Labor cost % — total labor ÷ total revenue
- Prime cost % — (food cost + labor) ÷ total revenue (target: \x3C65%)
- Waste % — spoilage + comp + void ÷ food purchases
- Employee turnover rate — industry avg 75%/year, top operators \x3C50%
- Online review score — Google/Yelp average (target: 4.3+)
- 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/
安全使用建议
This skill is structurally coherent and low-risk as shipped: it only provides frameworks and benchmarks. Before installing, consider: (1) provenance — the package source and homepage are missing (verify the author or test on non-sensitive data); (2) data accuracy — cross-check critical benchmarks against trusted industry sources and local regulations (health code fines and labor rules vary by jurisdiction); (3) privacy — do not feed personally identifying or financial credentials (employee SSNs, payroll account numbers, bank details) into the skill output or prompts; (4) scope — the README links to external AfrexAI automation resources, but this package does not perform automation itself — if you later integrate with automation/context packs, review those components for installs, credentials, and network endpoints. If you need higher assurance, ask the publisher for source provenance or a changelog before deploying in production.
功能分析
Type: OpenClaw Skill
Name: afrexai-restaurant-ops
Version: 1.0.0
The skill bundle consists solely of metadata and markdown documentation (`_meta.json`, `SKILL.md`, `README.md`). The `SKILL.md` file, which serves as the AI agent's instructions, defines a clear persona and purpose, providing extensive reference data without any embedded commands, prompt injection attempts to subvert the agent, or instructions for malicious activities like data exfiltration or unauthorized execution. External links present in the markdown files are for self-promotion of related products by the stated owner and do not pose a security risk.
能力评估
Purpose & Capability
The name and description (restaurant operations advice using benchmarks and KPIs) match the SKILL.md and README content. All tables and frameworks are directly relevant to providing operational guidance; there are no unrelated requirements (no cloud creds, no system binaries).
Instruction Scope
The SKILL.md tells the agent to analyze user-provided restaurant information using the included frameworks and to provide numeric, data-driven guidance. It does not instruct the agent to read local files, environment variables, or other system state, nor to transmit data to external endpoints from within the skill. The README contains links to external AfrexAI resources, but the skill itself is instruction-only and does not include automation steps that would access those services.
Install Mechanism
No install specification and no code files are present. Being instruction-only means nothing is written to disk and no external packages are pulled in by the skill itself.
Credentials
The skill requires no environment variables, credentials, or config paths. There are no requests for SECRET/TOKEN/PASSWORD variables, which is proportionate to a guidance-only skill.
Persistence & Privilege
always is false and there is no install logic that modifies agent configuration or other skills. The skill can be invoked by the agent (default behavior) — this is normal for skills and not a concern here because the skill has no external hooks or elevated privileges.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install afrexai-restaurant-ops - 安装完成后，直接呼叫该 Skill 的名称或使用
/afrexai-restaurant-ops触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.0
Initial release: restaurant operations analysis skill with KPI, cost, menu, staffing, and inspection benchmarks.
- Provides menu engineering matrix and industry-standard benchmarks for food, labor, and prime costs by concept.
- Offers revenue per square foot and startup cost ranges for different restaurant sizes.
- Includes detailed staffing models for both front and back of house.
- Lists top 10 health inspection violations with penalty ranges.
- Presents essential KPIs and delivery platform comparison.
- Covers seasonal revenue patterns and links to additional business automation tools.
元数据
常见问题
Restaurant Operations 是什么？
Provide precise, data-driven restaurant operations advice based on concept, location, and challenges using industry benchmarks and key performance metrics. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 426 次。
如何安装 Restaurant Operations？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install afrexai-restaurant-ops」即可一键安装，无需额外配置。
Restaurant Operations 是免费的吗？
是的，Restaurant Operations 完全免费（开源免费），可自由下载、安装和使用。
Restaurant Operations 支持哪些平台？
Restaurant Operations 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Restaurant Operations？
由 1kalin（@1kalin）开发并维护，当前版本 v1.0.0。
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