{
  "schemaVersion": "1.0",
  "item": {
    "slug": "afrexai-restaurant-ops",
    "name": "Restaurant Operations",
    "source": "tencent",
    "type": "skill",
    "category": "效率提升",
    "sourceUrl": "https://clawhub.ai/1kalin/afrexai-restaurant-ops",
    "canonicalUrl": "https://clawhub.ai/1kalin/afrexai-restaurant-ops",
    "targetPlatform": "OpenClaw"
  },
  "install": {
    "downloadMode": "redirect",
    "downloadUrl": "/downloads/afrexai-restaurant-ops",
    "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=afrexai-restaurant-ops",
    "sourcePlatform": "tencent",
    "targetPlatform": "OpenClaw",
    "installMethod": "Manual import",
    "extraction": "Extract archive",
    "prerequisites": [
      "OpenClaw"
    ],
    "packageFormat": "ZIP package",
    "includedAssets": [
      "README.md",
      "SKILL.md"
    ],
    "primaryDoc": "SKILL.md",
    "quickSetup": [
      "Download the package from Yavira.",
      "Extract the archive and review SKILL.md first.",
      "Import or place the package into your OpenClaw setup."
    ],
    "agentAssist": {
      "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.",
      "steps": [
        "Download the package from Yavira.",
        "Extract it into a folder your agent can access.",
        "Paste one of the prompts below and point your agent at the extracted folder."
      ],
      "prompts": [
        {
          "label": "New install",
          "body": "I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete."
        },
        {
          "label": "Upgrade existing",
          "body": "I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run."
        }
      ]
    },
    "sourceHealth": {
      "source": "tencent",
      "status": "healthy",
      "reason": "direct_download_ok",
      "recommendedAction": "download",
      "checkedAt": "2026-04-30T16:55:25.780Z",
      "expiresAt": "2026-05-07T16:55:25.780Z",
      "httpStatus": 200,
      "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=network",
      "contentType": "application/zip",
      "probeMethod": "head",
      "details": {
        "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=network",
        "contentDisposition": "attachment; filename=\"network-1.0.0.zip\"",
        "redirectLocation": null,
        "bodySnippet": null
      },
      "scope": "source",
      "summary": "Source download looks usable.",
      "detail": "Yavira can redirect you to the upstream package for this source.",
      "primaryActionLabel": "Download for OpenClaw",
      "primaryActionHref": "/downloads/afrexai-restaurant-ops"
    },
    "validation": {
      "installChecklist": [
        "Use the Yavira download entry.",
        "Review SKILL.md after the package is downloaded.",
        "Confirm the extracted package contains the expected setup assets."
      ],
      "postInstallChecks": [
        "Confirm the extracted package includes the expected docs or setup files.",
        "Validate the skill or prompts are available in your target agent workspace.",
        "Capture any manual follow-up steps the agent could not complete."
      ]
    },
    "downloadPageUrl": "https://openagent3.xyz/downloads/afrexai-restaurant-ops",
    "agentPageUrl": "https://openagent3.xyz/skills/afrexai-restaurant-ops/agent",
    "manifestUrl": "https://openagent3.xyz/skills/afrexai-restaurant-ops/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/afrexai-restaurant-ops/agent.md"
  },
  "agentAssist": {
    "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.",
    "steps": [
      "Download the package from Yavira.",
      "Extract it into a folder your agent can access.",
      "Paste one of the prompts below and point your agent at the extracted folder."
    ],
    "prompts": [
      {
        "label": "New install",
        "body": "I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete."
      },
      {
        "label": "Upgrade existing",
        "body": "I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run."
      }
    ]
  },
  "documentation": {
    "source": "clawhub",
    "primaryDoc": "SKILL.md",
    "sections": [
      {
        "title": "Restaurant Operations Intelligence",
        "body": "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."
      },
      {
        "title": "How to Use",
        "body": "User describes their restaurant (type, size, location, stage)\nAnalyze using the frameworks below\nProvide specific numbers, not vague advice"
      },
      {
        "title": "Menu Engineering Matrix",
        "body": "CategoryFood Cost %Menu Mix %ActionStars<30%>15%Promote heavily, prime menu placementPlowhorses>30%>15%Re-engineer recipe, reduce portions, raise pricePuzzles<30%<15%Reposition, rename, server trainingDogs>30%<15%Remove or replace immediately"
      },
      {
        "title": "Food Cost Benchmarks by Concept",
        "body": "ConceptTarget Food CostTarget Labor CostTarget Prime CostFine Dining28-32%30-35%60-65%Casual Dining28-35%25-30%55-65%Fast Casual25-30%22-28%50-58%QSR/Fast Food25-32%20-25%48-55%Pizza20-28%22-28%45-55%Coffee Shop/Bakery25-35%30-40%58-70%Bar/Nightclub18-24%20-28%42-50%Food Truck28-35%25-30%55-65%Ghost Kitchen28-35%15-22%45-55%"
      },
      {
        "title": "Revenue Per Square Foot Benchmarks",
        "body": "ConceptLowAverageTop 25%Fine Dining$250$400$600+Casual Dining$150$250$400Fast Casual$300$500$800+QSR$400$600$1,000+Coffee Shop$200$350$500+"
      },
      {
        "title": "Front of House (per 50 seats)",
        "body": "RoleLunchDinnerWeekend PeakServers3-45-67-8Bartender11-22-3Host11-22Busser1-22-33-4Manager111-2"
      },
      {
        "title": "Back of House (per $15K daily revenue)",
        "body": "RoleCountHourly RangeExecutive Chef1Salary $55K-$85KSous Chef1-2$18-$28Line Cook3-5$15-$22Prep Cook2-3$13-$18Dishwasher1-2$12-$16"
      },
      {
        "title": "Health Department Inspection — Top 10 Violations",
        "body": "Improper holding temperatures — hot food <135°F, cold food >41°F\nInadequate handwashing — no soap, no paper towels, infrequent washing\nCross-contamination — raw proteins stored above ready-to-eat\nNo certified food manager — required in most jurisdictions\nPest evidence — droppings, nesting, live insects\nExpired food items — no date labels on prep items\nImproper cooling — must cool from 135°F to 70°F in 2 hours, then to 41°F in 4 more\nChemical storage — cleaning chemicals stored near food\nEquipment sanitation — cutting boards, slicers not sanitized between uses\nEmployee illness policy — no written policy for reporting symptoms\n\nPenalty range: $100-$1,000 per violation. Repeat critical violations = temporary closure."
      },
      {
        "title": "Startup Cost Ranges",
        "body": "ItemSmall (<2,000 sqft)Medium (2-4K sqft)Large (4K+ sqft)Lease deposit$5K-$15K$15K-$40K$40K-$100KBuild-out$50K-$150K$150K-$400K$400K-$1M+Kitchen equipment$30K-$75K$75K-$200K$200K-$500KPOS system$3K-$10K$10K-$25K$20K-$50KInitial inventory$5K-$15K$15K-$30K$30K-$60KLicenses/permits$2K-$10K$5K-$15K$10K-$25KLiquor license$3K-$50K+$3K-$50K+$3K-$50K+Marketing launch$5K-$15K$15K-$30K$30K-$75KWorking capital (3mo)$30K-$60K$60K-$150K$150K-$300KTotal$133K-$400K$348K-$940K$883K-$2.2M"
      },
      {
        "title": "KPIs Every Restaurant Should Track",
        "body": "Revenue per available seat hour (RevPASH) — revenue ÷ (seats × hours open)\nTable turn time — average minutes from seat to check close\nAverage check size — total revenue ÷ covers\nFood cost % — COGS ÷ food revenue\nLabor cost % — total labor ÷ total revenue\nPrime cost % — (food cost + labor) ÷ total revenue (target: <65%)\nWaste % — spoilage + comp + void ÷ food purchases\nEmployee turnover rate — industry avg 75%/year, top operators <50%\nOnline review score — Google/Yelp average (target: 4.3+)\nBreak-even point — fixed costs ÷ (1 - variable cost %)"
      },
      {
        "title": "Delivery & Third-Party Platforms",
        "body": "PlatformCommissionProsConsDoorDash15-30%Largest US market shareHigh commission, owns customer dataUber Eats15-30%Global reachSame issues as aboveGrubhub15-30%Strong in NortheastDeclining market shareDirect (own site)0-5%Own customer data, lower costMust drive own trafficGhost kitchen modelN/ANo FOH cost, multi-brandNo dine-in revenue, brand building harder\n\nRule of thumb: If delivery >20% of revenue, negotiate commission or invest in direct ordering."
      },
      {
        "title": "Seasonal Revenue Patterns (US Average)",
        "body": "MonthIndex (100 = avg)NotesJanuary80-85Post-holiday slump, New Year dietsFebruary85-95Valentine's Day spikeMarch95-100Spring break, St. Patrick's DayApril100-105Easter, patio season startsMay105-115Mother's Day (busiest restaurant day), graduationJune105-110Summer dining, tourismJuly100-1054th of July, vacation slowdownsAugust95-100Back to school transitionSeptember95-100Labor Day, routine resumesOctober100-105Fall dining, HalloweenNovember105-115Thanksgiving week huge, otherwise averageDecember110-120Holiday parties, NYE"
      },
      {
        "title": "Need More?",
        "body": "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/\n\nBuilt by AfrexAI — turning operational data into revenue. https://afrexai-cto.github.io/ai-revenue-calculator/"
      }
    ],
    "body": "Restaurant Operations Intelligence\n\nYou are a restaurant operations analyst. When the user describes their restaurant concept, location, or operational challenge, provide data-driven guidance using the reference below.\n\nHow to Use\nUser describes their restaurant (type, size, location, stage)\nAnalyze using the frameworks below\nProvide specific numbers, not vague advice\nMenu Engineering Matrix\nCategory\tFood Cost %\tMenu Mix %\tAction\nStars\t<30%\t>15%\tPromote heavily, prime menu placement\nPlowhorses\t>30%\t>15%\tRe-engineer recipe, reduce portions, raise price\nPuzzles\t<30%\t<15%\tReposition, rename, server training\nDogs\t>30%\t<15%\tRemove or replace immediately\nFood Cost Benchmarks by Concept\nConcept\tTarget Food Cost\tTarget Labor Cost\tTarget Prime Cost\nFine Dining\t28-32%\t30-35%\t60-65%\nCasual Dining\t28-35%\t25-30%\t55-65%\nFast Casual\t25-30%\t22-28%\t50-58%\nQSR/Fast Food\t25-32%\t20-25%\t48-55%\nPizza\t20-28%\t22-28%\t45-55%\nCoffee Shop/Bakery\t25-35%\t30-40%\t58-70%\nBar/Nightclub\t18-24%\t20-28%\t42-50%\nFood Truck\t28-35%\t25-30%\t55-65%\nGhost Kitchen\t28-35%\t15-22%\t45-55%\nRevenue Per Square Foot Benchmarks\nConcept\tLow\tAverage\tTop 25%\nFine Dining\t$250\t$400\t$600+\nCasual Dining\t$150\t$250\t$400\nFast Casual\t$300\t$500\t$800+\nQSR\t$400\t$600\t$1,000+\nCoffee Shop\t$200\t$350\t$500+\nStaffing Models\nFront of House (per 50 seats)\nRole\tLunch\tDinner\tWeekend Peak\nServers\t3-4\t5-6\t7-8\nBartender\t1\t1-2\t2-3\nHost\t1\t1-2\t2\nBusser\t1-2\t2-3\t3-4\nManager\t1\t1\t1-2\nBack of House (per $15K daily revenue)\nRole\tCount\tHourly Range\nExecutive Chef\t1\tSalary $55K-$85K\nSous Chef\t1-2\t$18-$28\nLine Cook\t3-5\t$15-$22\nPrep Cook\t2-3\t$13-$18\nDishwasher\t1-2\t$12-$16\nHealth Department Inspection — Top 10 Violations\nImproper holding temperatures — hot food <135°F, cold food >41°F\nInadequate handwashing — no soap, no paper towels, infrequent washing\nCross-contamination — raw proteins stored above ready-to-eat\nNo certified food manager — required in most jurisdictions\nPest evidence — droppings, nesting, live insects\nExpired food items — no date labels on prep items\nImproper cooling — must cool from 135°F to 70°F in 2 hours, then to 41°F in 4 more\nChemical storage — cleaning chemicals stored near food\nEquipment sanitation — cutting boards, slicers not sanitized between uses\nEmployee illness policy — no written policy for reporting symptoms\n\nPenalty range: $100-$1,000 per violation. Repeat critical violations = temporary closure.\n\nStartup Cost Ranges\nItem\tSmall (<2,000 sqft)\tMedium (2-4K sqft)\tLarge (4K+ sqft)\nLease deposit\t$5K-$15K\t$15K-$40K\t$40K-$100K\nBuild-out\t$50K-$150K\t$150K-$400K\t$400K-$1M+\nKitchen equipment\t$30K-$75K\t$75K-$200K\t$200K-$500K\nPOS system\t$3K-$10K\t$10K-$25K\t$20K-$50K\nInitial inventory\t$5K-$15K\t$15K-$30K\t$30K-$60K\nLicenses/permits\t$2K-$10K\t$5K-$15K\t$10K-$25K\nLiquor license\t$3K-$50K+\t$3K-$50K+\t$3K-$50K+\nMarketing launch\t$5K-$15K\t$15K-$30K\t$30K-$75K\nWorking capital (3mo)\t$30K-$60K\t$60K-$150K\t$150K-$300K\nTotal\t$133K-$400K\t$348K-$940K\t$883K-$2.2M\nKPIs Every Restaurant Should Track\nRevenue per available seat hour (RevPASH) — revenue ÷ (seats × hours open)\nTable turn time — average minutes from seat to check close\nAverage check size — total revenue ÷ covers\nFood cost % — COGS ÷ food revenue\nLabor cost % — total labor ÷ total revenue\nPrime cost % — (food cost + labor) ÷ total revenue (target: <65%)\nWaste % — spoilage + comp + void ÷ food purchases\nEmployee turnover rate — industry avg 75%/year, top operators <50%\nOnline review score — Google/Yelp average (target: 4.3+)\nBreak-even point — fixed costs ÷ (1 - variable cost %)\nDelivery & Third-Party Platforms\nPlatform\tCommission\tPros\tCons\nDoorDash\t15-30%\tLargest US market share\tHigh commission, owns customer data\nUber Eats\t15-30%\tGlobal reach\tSame issues as above\nGrubhub\t15-30%\tStrong in Northeast\tDeclining market share\nDirect (own site)\t0-5%\tOwn customer data, lower cost\tMust drive own traffic\nGhost kitchen model\tN/A\tNo FOH cost, multi-brand\tNo dine-in revenue, brand building harder\n\nRule of thumb: If delivery >20% of revenue, negotiate commission or invest in direct ordering.\n\nSeasonal Revenue Patterns (US Average)\nMonth\tIndex (100 = avg)\tNotes\nJanuary\t80-85\tPost-holiday slump, New Year diets\nFebruary\t85-95\tValentine's Day spike\nMarch\t95-100\tSpring break, St. Patrick's Day\nApril\t100-105\tEaster, patio season starts\nMay\t105-115\tMother's Day (busiest restaurant day), graduation\nJune\t105-110\tSummer dining, tourism\nJuly\t100-105\t4th of July, vacation slowdowns\nAugust\t95-100\tBack to school transition\nSeptember\t95-100\tLabor Day, routine resumes\nOctober\t100-105\tFall dining, Halloween\nNovember\t105-115\tThanksgiving week huge, otherwise average\nDecember\t110-120\tHoliday parties, NYE\nNeed More?\n\nThis 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/\n\nBuilt by AfrexAI — turning operational data into revenue. https://afrexai-cto.github.io/ai-revenue-calculator/"
  },
  "trust": {
    "sourceLabel": "tencent",
    "provenanceUrl": "https://clawhub.ai/1kalin/afrexai-restaurant-ops",
    "publisherUrl": "https://clawhub.ai/1kalin/afrexai-restaurant-ops",
    "owner": "1kalin",
    "version": "1.0.0",
    "license": null,
    "verificationStatus": "Indexed source record"
  },
  "links": {
    "detailUrl": "https://openagent3.xyz/skills/afrexai-restaurant-ops",
    "downloadUrl": "https://openagent3.xyz/downloads/afrexai-restaurant-ops",
    "agentUrl": "https://openagent3.xyz/skills/afrexai-restaurant-ops/agent",
    "manifestUrl": "https://openagent3.xyz/skills/afrexai-restaurant-ops/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/afrexai-restaurant-ops/agent.md"
  }
}