{
  "schemaVersion": "1.0",
  "item": {
    "slug": "food-delivery",
    "name": "Food Delivery",
    "source": "tencent",
    "type": "skill",
    "category": "内容创作",
    "sourceUrl": "https://clawhub.ai/ivangdavila/food-delivery",
    "canonicalUrl": "https://clawhub.ai/ivangdavila/food-delivery",
    "targetPlatform": "OpenClaw"
  },
  "install": {
    "downloadMode": "redirect",
    "downloadUrl": "/downloads/food-delivery",
    "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=food-delivery",
    "sourcePlatform": "tencent",
    "targetPlatform": "OpenClaw",
    "installMethod": "Manual import",
    "extraction": "Extract archive",
    "prerequisites": [
      "OpenClaw"
    ],
    "packageFormat": "ZIP package",
    "includedAssets": [
      "SKILL.md",
      "decisions.md",
      "memory-template.md",
      "ordering.md",
      "traps.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. 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. Summarize what changed and any follow-up checks I should run."
        }
      ]
    },
    "sourceHealth": {
      "source": "tencent",
      "status": "healthy",
      "reason": "direct_download_ok",
      "recommendedAction": "download",
      "checkedAt": "2026-04-23T16:43:11.935Z",
      "expiresAt": "2026-04-30T16:43:11.935Z",
      "httpStatus": 200,
      "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=4claw-imageboard",
      "contentType": "application/zip",
      "probeMethod": "head",
      "details": {
        "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=4claw-imageboard",
        "contentDisposition": "attachment; filename=\"4claw-imageboard-1.0.1.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/food-delivery"
    },
    "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/food-delivery",
    "agentPageUrl": "https://openagent3.xyz/skills/food-delivery/agent",
    "manifestUrl": "https://openagent3.xyz/skills/food-delivery/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/food-delivery/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. 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. Summarize what changed and any follow-up checks I should run."
      }
    ]
  },
  "documentation": {
    "source": "clawhub",
    "primaryDoc": "SKILL.md",
    "sections": [
      {
        "title": "When to Use",
        "body": "User wants their agent to handle the entire food ordering process — from deciding what to eat, through comparing options, to placing the actual order. Agent learns preferences over time and makes increasingly better choices."
      },
      {
        "title": "Architecture",
        "body": "Memory lives in ~/food-delivery/. See memory-template.md for setup.\n\n~/food-delivery/\n├── memory.md          # Core preferences, restrictions, defaults\n├── restaurants.md     # Restaurant ratings, dishes, notes\n├── orders.md          # Recent orders for variety tracking\n└── people.md          # Household/group member preferences\n\nUser creates these files. Templates in memory-template.md."
      },
      {
        "title": "Quick Reference",
        "body": "TopicFileMemory setupmemory-template.mdDecision frameworkdecisions.mdOrdering workflowordering.mdCommon trapstraps.md"
      },
      {
        "title": "Data Storage",
        "body": "All data stored in ~/food-delivery/. Create on first use:\n\nmkdir -p ~/food-delivery"
      },
      {
        "title": "Scope",
        "body": "This skill handles:\n\nLearning cuisine and taste preferences\nStoring restaurant ratings and dish notes\nComparing prices across delivery platforms\nFinding active promotions and coupons\nPlacing orders via browser automation\nTracking recent orders for variety\nManaging household member preferences\nCoordinating group orders\n\nUser provides:\n\nDelivery app credentials (stored in their browser/app)\nDelivery address (configured in their apps)\nPayment methods (configured in their apps)"
      },
      {
        "title": "Self-Modification",
        "body": "This skill NEVER modifies its own SKILL.md.\nAll learned data stored in ~/food-delivery/ files."
      },
      {
        "title": "1. Learn Preferences Explicitly",
        "body": "User saysStore in memory.md\"I'm vegetarian\"restriction: vegetarian\"I love spicy food\"preference: spice_level=high\"Allergic to shellfish\"CRITICAL: shellfish (always filter)\"I don't like olives\"avoid: olives\"Budget around $20\"default_budget: $20\"Usually order dinner around 7pm\"default_time: 19:00"
      },
      {
        "title": "2. Restriction Hierarchy",
        "body": "CRITICAL (allergies, medical) → ALWAYS filter, never suggest\nFIRM (religious, ethical, diet) → filter unless user overrides\nPREFERENCE (taste) → consider but flexible\n\nFor CRITICAL restrictions:\n\nAdd note to EVERY order specifying the allergy\nVerify restaurant can accommodate\nNever suggest \"you could try it anyway\""
      },
      {
        "title": "3. The Decision Flow",
        "body": "When user asks to order food:\n\nStep 1: Context\n\nWhat time is it? (breakfast/lunch/dinner)\nWhat day? (weekday functional vs weekend exploratory)\nAny stated mood or occasion?\nHow many people?\n\nStep 2: Filter\n\nRemove anything violating CRITICAL restrictions\nRemove recently repeated (variety protection)\nRemove closed restaurants\nApply budget constraints\n\nStep 3: Compare\n\nCheck same restaurant across platforms\nFind active promos/coupons\nCalculate total cost (food + delivery + fees)\n\nStep 4: Present\n\nShow 2-3 options maximum\nInclude reasoning for each\nShow price comparison if relevant\nRecommend one based on user history\n\nStep 5: Confirm & Order\n\nGet explicit confirmation\nPlace order via browser\nConfirm order placed with ETA"
      },
      {
        "title": "4. Variety Protection",
        "body": "Track in orders.md:\n\nLast 14 days of orders (restaurant + cuisine type)\n\nTriggers:\n\nSame restaurant 3x in 7 days → \"You've ordered from [X] a lot. Want to try something similar?\"\nSame cuisine 4x in 7 days → suggest different category\nHaven't tried category user likes in 2+ weeks → suggest it"
      },
      {
        "title": "5. Price Optimization",
        "body": "Before ordering:\n\nCheck restaurant on all user's delivery apps\nCompare base prices (often differ by platform)\nCheck for active coupons/promos\nFactor in delivery fees and service charges\nRecommend cheapest option for same food\n\nTell user: \"Same order is $4 cheaper on [Platform] today\""
      },
      {
        "title": "6. Group Orders",
        "body": "When ordering for multiple people:\n\nLoad ~/food-delivery/people.md for known preferences\nCollect any new restrictions\nFind intersection cuisine (works for everyone)\nSuggest variety restaurants (broad menus)\nCalculate fair split if needed\n\nDefault crowd-pleasers when no consensus:\n\nPizza (customizable)\nBurgers (something for everyone)\nTacos (variety of fillings)\nChinese (range of dishes)\nIndian (vegetarian options)"
      },
      {
        "title": "7. Context Adaptation",
        "body": "ContextBehavior\"I'm tired\"Comfort food, familiar favorites\"Celebrating\"Higher-end, special occasion spots\"In a hurry\"Fastest delivery, simple orders\"Working lunch\"Quick, not messy, productive-friendly\"Date night\"Quality over speed, ambiance matters\"Hungover\"Greasy comfort, hydrating, gentle\"Post-workout\"Protein-heavy, healthier optionsRainy dayWarn about longer delivery timesFriday nightCan wait for qualitySunday morningBrunch options, recovery mode"
      },
      {
        "title": "8. Proactive Suggestions",
        "body": "When appropriate (not spammy):\n\nNotify of flash sales on favorite restaurants\nRemind of unused loyalty points\nSuggest reordering past successes\nMention new restaurants matching preferences"
      },
      {
        "title": "9. Order Execution",
        "body": "Via browser automation:\n\nOpen user's preferred delivery app\nNavigate to restaurant\nAdd items to cart\nApply any coupons found\nVerify delivery address\nConfirm order total with user\nPlace order\nReport confirmation and ETA\n\nAlways confirm before final checkout."
      },
      {
        "title": "10. Problem Handling",
        "body": "If order has issues:\n\nMissing items → help file complaint\nWrong items → help request refund\nLate delivery → track and communicate\nQuality issues → record in restaurant notes"
      },
      {
        "title": "Stored Locally (in ~/food-delivery/)",
        "body": "Cuisine preferences and restrictions\nRestaurant ratings and dish notes\nRecent order log (variety tracking)\nHousehold member preferences\nBudget defaults"
      },
      {
        "title": "User Manages (in their apps)",
        "body": "Delivery addresses\nPayment methods\nAccount credentials"
      },
      {
        "title": "Agent Does NOT Store",
        "body": "Credit card numbers\nExact addresses\nAccount passwords\nOrder receipts with payment details"
      }
    ],
    "body": "When to Use\n\nUser wants their agent to handle the entire food ordering process — from deciding what to eat, through comparing options, to placing the actual order. Agent learns preferences over time and makes increasingly better choices.\n\nArchitecture\n\nMemory lives in ~/food-delivery/. See memory-template.md for setup.\n\n~/food-delivery/\n├── memory.md          # Core preferences, restrictions, defaults\n├── restaurants.md     # Restaurant ratings, dishes, notes\n├── orders.md          # Recent orders for variety tracking\n└── people.md          # Household/group member preferences\n\n\nUser creates these files. Templates in memory-template.md.\n\nQuick Reference\nTopic\tFile\nMemory setup\tmemory-template.md\nDecision framework\tdecisions.md\nOrdering workflow\tordering.md\nCommon traps\ttraps.md\nData Storage\n\nAll data stored in ~/food-delivery/. Create on first use:\n\nmkdir -p ~/food-delivery\n\nScope\n\nThis skill handles:\n\nLearning cuisine and taste preferences\nStoring restaurant ratings and dish notes\nComparing prices across delivery platforms\nFinding active promotions and coupons\nPlacing orders via browser automation\nTracking recent orders for variety\nManaging household member preferences\nCoordinating group orders\n\nUser provides:\n\nDelivery app credentials (stored in their browser/app)\nDelivery address (configured in their apps)\nPayment methods (configured in their apps)\nSelf-Modification\n\nThis skill NEVER modifies its own SKILL.md. All learned data stored in ~/food-delivery/ files.\n\nCore Rules\n1. Learn Preferences Explicitly\nUser says\tStore in memory.md\n\"I'm vegetarian\"\trestriction: vegetarian\n\"I love spicy food\"\tpreference: spice_level=high\n\"Allergic to shellfish\"\tCRITICAL: shellfish (always filter)\n\"I don't like olives\"\tavoid: olives\n\"Budget around $20\"\tdefault_budget: $20\n\"Usually order dinner around 7pm\"\tdefault_time: 19:00\n2. Restriction Hierarchy\nCRITICAL (allergies, medical) → ALWAYS filter, never suggest\nFIRM (religious, ethical, diet) → filter unless user overrides\nPREFERENCE (taste) → consider but flexible\n\n\nFor CRITICAL restrictions:\n\nAdd note to EVERY order specifying the allergy\nVerify restaurant can accommodate\nNever suggest \"you could try it anyway\"\n3. The Decision Flow\n\nWhen user asks to order food:\n\nStep 1: Context\n\nWhat time is it? (breakfast/lunch/dinner)\nWhat day? (weekday functional vs weekend exploratory)\nAny stated mood or occasion?\nHow many people?\n\nStep 2: Filter\n\nRemove anything violating CRITICAL restrictions\nRemove recently repeated (variety protection)\nRemove closed restaurants\nApply budget constraints\n\nStep 3: Compare\n\nCheck same restaurant across platforms\nFind active promos/coupons\nCalculate total cost (food + delivery + fees)\n\nStep 4: Present\n\nShow 2-3 options maximum\nInclude reasoning for each\nShow price comparison if relevant\nRecommend one based on user history\n\nStep 5: Confirm & Order\n\nGet explicit confirmation\nPlace order via browser\nConfirm order placed with ETA\n4. Variety Protection\n\nTrack in orders.md:\n\nLast 14 days of orders (restaurant + cuisine type)\n\nTriggers:\n\nSame restaurant 3x in 7 days → \"You've ordered from [X] a lot. Want to try something similar?\"\nSame cuisine 4x in 7 days → suggest different category\nHaven't tried category user likes in 2+ weeks → suggest it\n5. Price Optimization\n\nBefore ordering:\n\nCheck restaurant on all user's delivery apps\nCompare base prices (often differ by platform)\nCheck for active coupons/promos\nFactor in delivery fees and service charges\nRecommend cheapest option for same food\n\nTell user: \"Same order is $4 cheaper on [Platform] today\"\n\n6. Group Orders\n\nWhen ordering for multiple people:\n\nLoad ~/food-delivery/people.md for known preferences\nCollect any new restrictions\nFind intersection cuisine (works for everyone)\nSuggest variety restaurants (broad menus)\nCalculate fair split if needed\n\nDefault crowd-pleasers when no consensus:\n\nPizza (customizable)\nBurgers (something for everyone)\nTacos (variety of fillings)\nChinese (range of dishes)\nIndian (vegetarian options)\n7. Context Adaptation\nContext\tBehavior\n\"I'm tired\"\tComfort food, familiar favorites\n\"Celebrating\"\tHigher-end, special occasion spots\n\"In a hurry\"\tFastest delivery, simple orders\n\"Working lunch\"\tQuick, not messy, productive-friendly\n\"Date night\"\tQuality over speed, ambiance matters\n\"Hungover\"\tGreasy comfort, hydrating, gentle\n\"Post-workout\"\tProtein-heavy, healthier options\nRainy day\tWarn about longer delivery times\nFriday night\tCan wait for quality\nSunday morning\tBrunch options, recovery mode\n8. Proactive Suggestions\n\nWhen appropriate (not spammy):\n\nNotify of flash sales on favorite restaurants\nRemind of unused loyalty points\nSuggest reordering past successes\nMention new restaurants matching preferences\n9. Order Execution\n\nVia browser automation:\n\nOpen user's preferred delivery app\nNavigate to restaurant\nAdd items to cart\nApply any coupons found\nVerify delivery address\nConfirm order total with user\nPlace order\nReport confirmation and ETA\n\nAlways confirm before final checkout.\n\n10. Problem Handling\n\nIf order has issues:\n\nMissing items → help file complaint\nWrong items → help request refund\nLate delivery → track and communicate\nQuality issues → record in restaurant notes\nBoundaries\nStored Locally (in ~/food-delivery/)\nCuisine preferences and restrictions\nRestaurant ratings and dish notes\nRecent order log (variety tracking)\nHousehold member preferences\nBudget defaults\nUser Manages (in their apps)\nDelivery addresses\nPayment methods\nAccount credentials\nAgent Does NOT Store\nCredit card numbers\nExact addresses\nAccount passwords\nOrder receipts with payment details"
  },
  "trust": {
    "sourceLabel": "tencent",
    "provenanceUrl": "https://clawhub.ai/ivangdavila/food-delivery",
    "publisherUrl": "https://clawhub.ai/ivangdavila/food-delivery",
    "owner": "ivangdavila",
    "version": "1.0.0",
    "license": null,
    "verificationStatus": "Indexed source record"
  },
  "links": {
    "detailUrl": "https://openagent3.xyz/skills/food-delivery",
    "downloadUrl": "https://openagent3.xyz/downloads/food-delivery",
    "agentUrl": "https://openagent3.xyz/skills/food-delivery/agent",
    "manifestUrl": "https://openagent3.xyz/skills/food-delivery/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/food-delivery/agent.md"
  }
}