{
  "schemaVersion": "1.0",
  "item": {
    "slug": "food",
    "name": "Food Tracker",
    "source": "tencent",
    "type": "skill",
    "category": "AI 智能",
    "sourceUrl": "https://clawhub.ai/ivangdavila/food",
    "canonicalUrl": "https://clawhub.ai/ivangdavila/food",
    "targetPlatform": "OpenClaw"
  },
  "install": {
    "downloadMode": "redirect",
    "downloadUrl": "/downloads/food",
    "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=food",
    "sourcePlatform": "tencent",
    "targetPlatform": "OpenClaw",
    "installMethod": "Manual import",
    "extraction": "Extract archive",
    "prerequisites": [
      "OpenClaw"
    ],
    "packageFormat": "ZIP package",
    "includedAssets": [
      "SKILL.md",
      "processing.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": "2026-04-30T16:55:25.780Z",
      "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/food"
    },
    "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",
    "agentPageUrl": "https://openagent3.xyz/skills/food/agent",
    "manifestUrl": "https://openagent3.xyz/skills/food/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/food/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": "Intelligent Food Absorption",
        "body": "This skill absorbs ANY food input, auto-classifies it, and organizes for insights.\n\nRules:\n\nAuto-detect input type: meal photo, nutrition label, recipe, menu, text\nExtract and structure: items, portions, context, nutrition when visible\nTag everything: #meal, #recipe, #product, #restaurant, #inventory\nOffer analysis: \"Want nutrition estimate?\" — don't force it\nBuild personal database: scanned labels, frequent meals, saved recipes\nProvide insights: patterns, variety, timing, correlations\nRemember restrictions permanently, flag conflicts proactively\nFor detailed macro tracking → complement with calories skill\nCheck processing.md for how each input type is handled"
      },
      {
        "title": "Memory Storage",
        "body": "All user data persists in: ~/food/memory.md\n\nFormat:\n\n### Preferences\n<!-- Their food preferences and restrictions. Format: \"item: type\" -->\n<!-- Examples: nuts: allergy, gluten: intolerance, vegetarian: choice -->\n\n### Products\n<!-- Scanned/saved products for quick-log. Format: \"product: cal/serving\" -->\n<!-- Examples: Hacendado yogurt: 120/170g, Oatly oat milk: 45/100ml -->\n\n### Patterns\n<!-- Detected eating patterns. Format: \"pattern\" -->\n<!-- Examples: breakfast ~8am, snacks after 10pm, eats out Fridays -->\n\n### Places\n<!-- Restaurants and spots. Format: \"place: notes\" -->\n<!-- Examples: Noma: loved fermented plum, Local Thai: go-to takeout -->\n\n### Recipes\n<!-- Saved recipes. Format: \"dish: key info\" -->\n<!-- Examples: quick hummus: chickpeas+tahini+lemon 5min, Sunday roast: 2h -->\n\nEmpty sections = no data yet. Absorb, classify, organize.\n\nInsights provided: Weekly variety score, meal timing patterns, frequent foods, eating out ratio, nutrition estimates when asked. Not medical advice."
      }
    ],
    "body": "Intelligent Food Absorption\n\nThis skill absorbs ANY food input, auto-classifies it, and organizes for insights.\n\nRules:\n\nAuto-detect input type: meal photo, nutrition label, recipe, menu, text\nExtract and structure: items, portions, context, nutrition when visible\nTag everything: #meal, #recipe, #product, #restaurant, #inventory\nOffer analysis: \"Want nutrition estimate?\" — don't force it\nBuild personal database: scanned labels, frequent meals, saved recipes\nProvide insights: patterns, variety, timing, correlations\nRemember restrictions permanently, flag conflicts proactively\nFor detailed macro tracking → complement with calories skill\nCheck processing.md for how each input type is handled\nMemory Storage\n\nAll user data persists in: ~/food/memory.md\n\nFormat:\n\n### Preferences\n<!-- Their food preferences and restrictions. Format: \"item: type\" -->\n<!-- Examples: nuts: allergy, gluten: intolerance, vegetarian: choice -->\n\n### Products\n<!-- Scanned/saved products for quick-log. Format: \"product: cal/serving\" -->\n<!-- Examples: Hacendado yogurt: 120/170g, Oatly oat milk: 45/100ml -->\n\n### Patterns\n<!-- Detected eating patterns. Format: \"pattern\" -->\n<!-- Examples: breakfast ~8am, snacks after 10pm, eats out Fridays -->\n\n### Places\n<!-- Restaurants and spots. Format: \"place: notes\" -->\n<!-- Examples: Noma: loved fermented plum, Local Thai: go-to takeout -->\n\n### Recipes\n<!-- Saved recipes. Format: \"dish: key info\" -->\n<!-- Examples: quick hummus: chickpeas+tahini+lemon 5min, Sunday roast: 2h -->\n\n\nEmpty sections = no data yet. Absorb, classify, organize.\n\nInsights provided: Weekly variety score, meal timing patterns, frequent foods, eating out ratio, nutrition estimates when asked. Not medical advice."
  },
  "trust": {
    "sourceLabel": "tencent",
    "provenanceUrl": "https://clawhub.ai/ivangdavila/food",
    "publisherUrl": "https://clawhub.ai/ivangdavila/food",
    "owner": "ivangdavila",
    "version": "1.0.1",
    "license": null,
    "verificationStatus": "Indexed source record"
  },
  "links": {
    "detailUrl": "https://openagent3.xyz/skills/food",
    "downloadUrl": "https://openagent3.xyz/downloads/food",
    "agentUrl": "https://openagent3.xyz/skills/food/agent",
    "manifestUrl": "https://openagent3.xyz/skills/food/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/food/agent.md"
  }
}