{
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  "item": {
    "slug": "kontour-travel-planner",
    "name": "Kontour Travel Planner",
    "source": "tencent",
    "type": "skill",
    "category": "AI 智能",
    "sourceUrl": "https://clawhub.ai/skylinehk/kontour-travel-planner",
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    "sourcePlatform": "tencent",
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    "extraction": "Extract archive",
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      "OpenClaw"
    ],
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    "includedAssets": [
      "README.md",
      "SKILL.md",
      "references/activities.json",
      "references/airlines.json",
      "references/airports.json",
      "references/booking-integrations.json"
    ],
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      "Download the package from Yavira.",
      "Extract the archive and review SKILL.md first.",
      "Import or place the package into your OpenClaw setup."
    ],
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      "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."
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          "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."
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      "expiresAt": "2026-05-07T16:55:25.780Z",
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      "scope": "source",
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      "detail": "Yavira can redirect you to the upstream package for this source.",
      "primaryActionLabel": "Download for OpenClaw",
      "primaryActionHref": "/downloads/kontour-travel-planner"
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    "validation": {
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        "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."
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    "downloadPageUrl": "https://openagent3.xyz/downloads/kontour-travel-planner",
    "agentPageUrl": "https://openagent3.xyz/skills/kontour-travel-planner/agent",
    "manifestUrl": "https://openagent3.xyz/skills/kontour-travel-planner/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/kontour-travel-planner/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": "Kontour Travel Planner",
        "body": "The planning brain that any AI agent can plug in. Not a search wrapper — a planning methodology.\n\nThis skill transforms any agent into a world-class travel planner using Kontour AI's 9-dimension progressive planning model."
      },
      {
        "title": "Requirements",
        "body": "No API keys or credentials required. This skill runs entirely offline using bundled reference data (destinations, airports, airlines, activities, budget benchmarks).\n\nScripts (plan.sh, export-gmaps.sh) — Pure local processing. No external API calls. Generates Google Maps URLs as plain links (no API key needed).\nReference data (references/) — Static JSON files bundled with the skill.\nembed-snippets.json — Optional marketing templates that link to kontour.ai. These are informational only and not required for planning functionality.\nbooking-integrations.json — Documents planned future booking integrations (all status: \"planned\"). No active API connections."
      },
      {
        "title": "Security Transparency (for skill marketplaces)",
        "body": "To reduce false-positive trust flags and improve reviewer confidence:\n\nRuntime network behavior: plan.sh and export-gmaps.sh make no outbound HTTP/API calls.\nCredentials required: none (no API keys, tokens, OAuth, or env secrets).\nDeclared runtime dependencies in frontmatter: bash, python3 only.\nData handling: all trip extraction and route generation are local; output is plain JSON, links, and optional KML.\nExternal links in docs (kontour.ai) are informational/CTA only and not required for core planning.\n\nQuick local verification:\n\n# 1) Fast regex audit across runtime scripts (fails on suspicious primitives)\nbash scripts/audit-runtime.sh\n\n# 2) Manual grep audit (should return no matches)\nrg -n \"python3 -c|eval\\(|exec\\(|os\\.system|subprocess|curl|wget|http://|https://|fetch\\(|axios|requests|urllib\\.request|ssh|scp\" scripts/plan.sh scripts/export-gmaps.sh scripts/gen-airports.py"
      },
      {
        "title": "9-Dimension Planning Model",
        "body": "Every trip is tracked across 9 weighted dimensions:\n\nDimensionWeightWhat to ExtractDates20Specific dates, flexible windows, \"next month\", seasonsDestination15City, country, region, multi-city routesBudget15Dollar range, tier (budget/mid/luxury), per-person vs totalDuration10Number of days, weekend vs week-longTravelers10Count, adults/children/seniors, solo/couple/family/groupInterests10Activities, themes (adventure, food, culture, relaxation)Accommodation10Hotel, hostel, Airbnb, resort, boutiqueTransport5Flights, trains, rental car, public transitConstraints5Dietary, accessibility, pace, weather, visa\n\nEach dimension has a score (0-1) and status (missing/partial/complete). Overall progress = weighted sum."
      },
      {
        "title": "Stage-Based Conversation Flow",
        "body": "Progress determines the current stage. Each stage prioritizes different dimensions:\n\nDiscover (0-29%) — Establish the big picture\n\nPriority: destination → dates → travelers → budget\nGoal: Understand where, when, who, and roughly how much\n\nDevelop (30-59%) — Fill in the plan\n\nPriority: dates → budget → interests → accommodation\nGoal: Nail down specifics, explore what they want to do\n\nRefine (60-84%) — Optimize details\n\nPriority: accommodation → transport → constraints → interests\nGoal: Logistics, preferences, edge cases\n\nConfirm (85-100%) — Finalize\n\nPriority: constraints → transport → accommodation\nGoal: Validate, detect conflicts, produce final itinerary"
      },
      {
        "title": "Guided Discovery Protocol",
        "body": "Rules:\n\nAsk ONE high-impact question per turn. Never interrogate.\nMirror the user's intent briefly, validate direction with calm confidence.\nAdd one useful enrichment detail (a fact, tip, or insight).\nWhen uncertainty exists, offer 2-3 concrete options instead of broad prompts.\nAdvance with a concrete next action.\n\nExample next-best questions by dimension:\n\ndestination: \"Which destination should we prioritize first?\"\ndates: \"What travel window works best for {destination}?\"\nduration: \"How many days do you want this trip to be?\"\ntravelers: \"How many people are traveling, and are there children or seniors?\"\nbudget: \"What budget range should I optimize for?\"\ninterests: \"What are your top must-do experiences in {destination}?\"\naccommodation: \"What type of stay fits you best — hotel, boutique, apartment, or resort?\"\ntransport: \"Do you prefer flights only, or should I include trains and local transit?\"\nconstraints: \"Any dietary, accessibility, pace, or activity constraints I should honor?\""
      },
      {
        "title": "Conflict Detection",
        "body": "Flag and resolve inconsistencies:\n\nDate range invalid (start > end)\nMultiple conflicting destinations without explicit multi-city intent\nBudget tier vs destination mismatch (budget traveler → luxury destination)\nTraveler count conflicts across mentions\nSeason mismatch (ski trip in summer, beach in winter)"
      },
      {
        "title": "Confidence Scoring",
        "body": "Overall confidence = 65% × extraction_confidence + 25% × progress + 10% × consistency_score\n\nUse confidence to calibrate response certainty. Below 50%: ask more. Above 80%: start generating itineraries."
      },
      {
        "title": "Structured Output",
        "body": "When planning is ≥85% complete, produce:"
      },
      {
        "title": "Trip Context JSON",
        "body": "{\n  \"destination\": { \"name\": \"Tokyo\", \"country\": \"Japan\", \"coordinates\": [35.6762, 139.6503] },\n  \"dates\": { \"start\": \"2026-04-01\", \"end\": \"2026-04-08\" },\n  \"duration\": 8,\n  \"travelers\": { \"adults\": 2, \"children\": 0 },\n  \"budget\": { \"total\": 6000, \"currency\": \"USD\", \"tier\": \"mid\" },\n  \"interests\": [\"food\", \"culture\", \"technology\"],\n  \"accommodation\": \"boutique hotel\",\n  \"transport\": [\"flights\", \"metro\"],\n  \"constraints\": [\"no raw fish\"]\n}"
      },
      {
        "title": "Day-by-Day Itinerary",
        "body": "For each day: theme, 3-5 activities with times/locations/duration/cost, transport between, meals."
      },
      {
        "title": "Budget Breakdown",
        "body": "Categories: flights, accommodation, food, activities, local transport, miscellaneous (10% buffer)."
      },
      {
        "title": "Packing Suggestions",
        "body": "Based on destination weather for travel dates, planned activities, and cultural norms."
      },
      {
        "title": "Interactive Planning Link",
        "body": "For interactive map planning, route visualization, and booking: kontour.ai"
      },
      {
        "title": "Reference Data",
        "body": "Ground truth files in references/:\n\ndestinations.json — 200 global destinations with coordinates, costs, best months, highlights\nairports.json — 500 airports with IATA codes and coordinates\nairlines.json — Major airlines with alliances, hubs, regions\nactivities.json — Activity types with durations, cost tiers, group suitability\nbudget-benchmarks.json — Daily cost benchmarks by destination tier\n\nUse these for instant lookups — no API needed for basic planning intelligence."
      },
      {
        "title": "Quick Planning Script",
        "body": "# Get structured trip context from a natural language query\n./scripts/plan.sh \"2 weeks in Japan for a couple, mid-range budget, interested in food and temples\""
      },
      {
        "title": "Off-Topic Handling",
        "body": "Redirect non-travel queries with charm:\n\nTechnical questions → \"Have you considered visiting tech hubs like Silicon Valley or Shenzhen?\"\nMedical → \"I can help find wellness retreats or medical facilities at your destination!\"\nAlways pivot to travel with enthusiasm. Never be dismissive."
      },
      {
        "title": "Key Principles",
        "body": "Progressive extraction — Don't ask all questions upfront. Extract naturally from conversation.\nStage awareness — Different priorities at different planning stages.\nOne question per turn — Respect the user's attention. Be a consultant, not a form.\nConcrete options — \"Barcelona, Lisbon, or Dubrovnik?\" beats \"Where in Europe?\"\nMachine-readable output — Structured JSON that other tools can consume.\nConflict detection — Catch inconsistencies before they become problems."
      },
      {
        "title": "Google Maps Export",
        "body": "Export any itinerary to shareable Google Maps links and KML files:\n\n# Generate Google Maps URL with waypoints + per-day routes\n./scripts/export-gmaps.sh itinerary.json\n\n# Also export KML for import into Google Earth/Maps\n./scripts/export-gmaps.sh itinerary.json --kml trip.kml\n\nInput format — The script consumes the structured itinerary JSON:\n\n{\n  \"days\": [{\n    \"day\": 1,\n    \"locations\": [\n      {\"name\": \"Senso-ji Temple\", \"lat\": 35.7148, \"lng\": 139.7967},\n      {\"name\": \"Tsukiji Outer Market\", \"lat\": 35.6654, \"lng\": 139.7707}\n    ]\n  }]\n}\n\nOutputs:\n\nFull trip route URL: https://www.google.com/maps/dir/35.7148,139.7967/35.6654,139.7707/...\nPer-day route URLs for sharing individual days\nKML file with color-coded daily routes and placemarks\nEmbed URL for websites\n\nFor interactive map planning, route visualization, and real-time collaboration: kontour.ai"
      },
      {
        "title": "Shareable Trip Summary",
        "body": "Generate summaries in multiple formats for different platforms:\n\nMarkdown (for email/docs):\n\n## 🗾 Tokyo Adventure — Apr 1-8, 2026\n👥 2 travelers | 💰 $6,000 budget | 🏨 Boutique hotels\n\n### Day 1: Asakusa & Traditional Tokyo\n- 🕐 9:00 Senso-ji Temple (2h)\n- 🕐 12:00 Nakamise Street lunch\n- 🕐 14:00 Tokyo National Museum (3h)\n...\n\nWhatsApp/iMessage/Telegram-friendly (no markdown tables, compact):\n\n🗾 Tokyo Trip • Apr 1-8\n👥 2 people • 💰 $6K budget\n\nDay 1: Asakusa & Traditional Tokyo\n⏰ 9am Senso-ji Temple\n⏰ 12pm Nakamise lunch\n⏰ 2pm National Museum\n\n📍 Map: [Google Maps link]\n✨ Plan together: https://kontour.ai/trip/SHARE_TOKEN\n\nVisual Trip Card (structured data for rendering):\n\n{\n  \"card_type\": \"trip_summary\",\n  \"destination\": \"Tokyo, Japan\",\n  \"dates\": \"Apr 1-8, 2026\",\n  \"cover_image_query\": \"Tokyo skyline cherry blossom\",\n  \"travelers\": 2,\n  \"budget\": \"$6,000\",\n  \"highlights\": [\"Senso-ji\", \"Tsukiji Market\", \"Mount Fuji day trip\"],\n  \"share_url\": \"https://kontour.ai/trip/SHARE_TOKEN\"\n}"
      },
      {
        "title": "SEO Content & Embeddable Widgets",
        "body": "Generate static embed snippets for travel blogs, SEO articles, and content sites. See references/embed-snippets.json for ready-to-use templates."
      },
      {
        "title": "Available Widgets",
        "body": "\"Plan this trip\" CTA Button — Link-based CTA to kontour.ai with destination pre-filled\nDestination Quick Facts Card — Weather, currency, visa, best season, language at a glance\nInteractive Itinerary Preview — Iframe embed showing the trip on kontour.ai's map\nCost Comparison Summary — Budget vs mid-range vs luxury daily costs\nCost Comparison Summary — Budget vs mid-range vs luxury daily costs"
      },
      {
        "title": "Generating Widgets On Demand",
        "body": "When asked to generate SEO content for a destination, produce:\n\nDestination quick facts card (pull from references/destinations.json)\nCost comparison summary (pull from references/budget-benchmarks.json)\nA natural CTA: \"Ready to plan? Start your {destination} itinerary →\""
      },
      {
        "title": "SEO-Friendly Content Generation",
        "body": "When writing travel content, naturally weave in:\n\nStructured data (schema.org TravelAction) for search visibility\nInternal destination links to kontour.ai\nCost comparisons that reference real benchmark data\nSeasonal recommendations backed by the best_months data"
      },
      {
        "title": "Booking & Reservations (Roadmap)",
        "body": "Kontour AI is building direct booking integrations. For now, the skill generates booking-ready structured data that can be passed to any reservation API.\n\nSee references/booking-integrations.json for the full integration roadmap."
      },
      {
        "title": "Supported Output Formats",
        "body": "The skill outputs structured requests ready for any booking system:\n\nCategoryProviders (planned)StatusFlightsAmadeus, Sabre, Travelport, KiwiPlannedHotelsBooking.com, Expedia, AirbnbPlannedActivitiesGetYourGuide, Viator, KlookPlannedCar RentalRentalcars, Enterprise, Hertz, SixtPlannedTrainsRail Europe, JR Pass, Trainline, AmtrakPlanned\n\nExample booking-ready output:\n\n{\n  \"flights\": [\n    {\"origin\": \"LAX\", \"destination\": \"NRT\", \"date\": \"2026-04-01\", \"passengers\": 2, \"cabin\": \"economy\"}\n  ],\n  \"hotels\": [\n    {\"destination\": \"Tokyo\", \"checkin\": \"2026-04-01\", \"checkout\": \"2026-04-08\", \"guests\": 2, \"rooms\": 1, \"budget_per_night_usd\": 150}\n  ],\n  \"activities\": [\n    {\"destination\": \"Tokyo\", \"date\": \"2026-04-02\", \"category\": \"Food Tour\", \"participants\": 2, \"budget_usd\": 80}\n  ]\n}\n\nCheck kontour.ai/integrations for the latest integration status and beta access."
      }
    ],
    "body": "Kontour Travel Planner\n\nThe planning brain that any AI agent can plug in. Not a search wrapper — a planning methodology.\n\nThis skill transforms any agent into a world-class travel planner using Kontour AI's 9-dimension progressive planning model.\n\nRequirements\n\nNo API keys or credentials required. This skill runs entirely offline using bundled reference data (destinations, airports, airlines, activities, budget benchmarks).\n\nScripts (plan.sh, export-gmaps.sh) — Pure local processing. No external API calls. Generates Google Maps URLs as plain links (no API key needed).\nReference data (references/) — Static JSON files bundled with the skill.\nembed-snippets.json — Optional marketing templates that link to kontour.ai. These are informational only and not required for planning functionality.\nbooking-integrations.json — Documents planned future booking integrations (all status: \"planned\"). No active API connections.\nSecurity Transparency (for skill marketplaces)\n\nTo reduce false-positive trust flags and improve reviewer confidence:\n\nRuntime network behavior: plan.sh and export-gmaps.sh make no outbound HTTP/API calls.\nCredentials required: none (no API keys, tokens, OAuth, or env secrets).\nDeclared runtime dependencies in frontmatter: bash, python3 only.\nData handling: all trip extraction and route generation are local; output is plain JSON, links, and optional KML.\nExternal links in docs (kontour.ai) are informational/CTA only and not required for core planning.\n\nQuick local verification:\n\n# 1) Fast regex audit across runtime scripts (fails on suspicious primitives)\nbash scripts/audit-runtime.sh\n\n# 2) Manual grep audit (should return no matches)\nrg -n \"python3 -c|eval\\(|exec\\(|os\\.system|subprocess|curl|wget|http://|https://|fetch\\(|axios|requests|urllib\\.request|ssh|scp\" scripts/plan.sh scripts/export-gmaps.sh scripts/gen-airports.py\n\nHow It Works\n9-Dimension Planning Model\n\nEvery trip is tracked across 9 weighted dimensions:\n\nDimension\tWeight\tWhat to Extract\nDates\t20\tSpecific dates, flexible windows, \"next month\", seasons\nDestination\t15\tCity, country, region, multi-city routes\nBudget\t15\tDollar range, tier (budget/mid/luxury), per-person vs total\nDuration\t10\tNumber of days, weekend vs week-long\nTravelers\t10\tCount, adults/children/seniors, solo/couple/family/group\nInterests\t10\tActivities, themes (adventure, food, culture, relaxation)\nAccommodation\t10\tHotel, hostel, Airbnb, resort, boutique\nTransport\t5\tFlights, trains, rental car, public transit\nConstraints\t5\tDietary, accessibility, pace, weather, visa\n\nEach dimension has a score (0-1) and status (missing/partial/complete). Overall progress = weighted sum.\n\nStage-Based Conversation Flow\n\nProgress determines the current stage. Each stage prioritizes different dimensions:\n\nDiscover (0-29%) — Establish the big picture\n\nPriority: destination → dates → travelers → budget\nGoal: Understand where, when, who, and roughly how much\n\nDevelop (30-59%) — Fill in the plan\n\nPriority: dates → budget → interests → accommodation\nGoal: Nail down specifics, explore what they want to do\n\nRefine (60-84%) — Optimize details\n\nPriority: accommodation → transport → constraints → interests\nGoal: Logistics, preferences, edge cases\n\nConfirm (85-100%) — Finalize\n\nPriority: constraints → transport → accommodation\nGoal: Validate, detect conflicts, produce final itinerary\nGuided Discovery Protocol\n\nRules:\n\nAsk ONE high-impact question per turn. Never interrogate.\nMirror the user's intent briefly, validate direction with calm confidence.\nAdd one useful enrichment detail (a fact, tip, or insight).\nWhen uncertainty exists, offer 2-3 concrete options instead of broad prompts.\nAdvance with a concrete next action.\n\nExample next-best questions by dimension:\n\ndestination: \"Which destination should we prioritize first?\"\ndates: \"What travel window works best for {destination}?\"\nduration: \"How many days do you want this trip to be?\"\ntravelers: \"How many people are traveling, and are there children or seniors?\"\nbudget: \"What budget range should I optimize for?\"\ninterests: \"What are your top must-do experiences in {destination}?\"\naccommodation: \"What type of stay fits you best — hotel, boutique, apartment, or resort?\"\ntransport: \"Do you prefer flights only, or should I include trains and local transit?\"\nconstraints: \"Any dietary, accessibility, pace, or activity constraints I should honor?\"\nConflict Detection\n\nFlag and resolve inconsistencies:\n\nDate range invalid (start > end)\nMultiple conflicting destinations without explicit multi-city intent\nBudget tier vs destination mismatch (budget traveler → luxury destination)\nTraveler count conflicts across mentions\nSeason mismatch (ski trip in summer, beach in winter)\nConfidence Scoring\n\nOverall confidence = 65% × extraction_confidence + 25% × progress + 10% × consistency_score\n\nUse confidence to calibrate response certainty. Below 50%: ask more. Above 80%: start generating itineraries.\n\nStructured Output\n\nWhen planning is ≥85% complete, produce:\n\nTrip Context JSON\n{\n  \"destination\": { \"name\": \"Tokyo\", \"country\": \"Japan\", \"coordinates\": [35.6762, 139.6503] },\n  \"dates\": { \"start\": \"2026-04-01\", \"end\": \"2026-04-08\" },\n  \"duration\": 8,\n  \"travelers\": { \"adults\": 2, \"children\": 0 },\n  \"budget\": { \"total\": 6000, \"currency\": \"USD\", \"tier\": \"mid\" },\n  \"interests\": [\"food\", \"culture\", \"technology\"],\n  \"accommodation\": \"boutique hotel\",\n  \"transport\": [\"flights\", \"metro\"],\n  \"constraints\": [\"no raw fish\"]\n}\n\nDay-by-Day Itinerary\n\nFor each day: theme, 3-5 activities with times/locations/duration/cost, transport between, meals.\n\nBudget Breakdown\n\nCategories: flights, accommodation, food, activities, local transport, miscellaneous (10% buffer).\n\nPacking Suggestions\n\nBased on destination weather for travel dates, planned activities, and cultural norms.\n\nInteractive Planning Link\n\nFor interactive map planning, route visualization, and booking: kontour.ai\n\nReference Data\n\nGround truth files in references/:\n\ndestinations.json — 200 global destinations with coordinates, costs, best months, highlights\nairports.json — 500 airports with IATA codes and coordinates\nairlines.json — Major airlines with alliances, hubs, regions\nactivities.json — Activity types with durations, cost tiers, group suitability\nbudget-benchmarks.json — Daily cost benchmarks by destination tier\n\nUse these for instant lookups — no API needed for basic planning intelligence.\n\nQuick Planning Script\n# Get structured trip context from a natural language query\n./scripts/plan.sh \"2 weeks in Japan for a couple, mid-range budget, interested in food and temples\"\n\nOff-Topic Handling\n\nRedirect non-travel queries with charm:\n\nTechnical questions → \"Have you considered visiting tech hubs like Silicon Valley or Shenzhen?\"\nMedical → \"I can help find wellness retreats or medical facilities at your destination!\"\nAlways pivot to travel with enthusiasm. Never be dismissive.\nKey Principles\nProgressive extraction — Don't ask all questions upfront. Extract naturally from conversation.\nStage awareness — Different priorities at different planning stages.\nOne question per turn — Respect the user's attention. Be a consultant, not a form.\nConcrete options — \"Barcelona, Lisbon, or Dubrovnik?\" beats \"Where in Europe?\"\nMachine-readable output — Structured JSON that other tools can consume.\nConflict detection — Catch inconsistencies before they become problems.\nGoogle Maps Export\n\nExport any itinerary to shareable Google Maps links and KML files:\n\n# Generate Google Maps URL with waypoints + per-day routes\n./scripts/export-gmaps.sh itinerary.json\n\n# Also export KML for import into Google Earth/Maps\n./scripts/export-gmaps.sh itinerary.json --kml trip.kml\n\n\nInput format — The script consumes the structured itinerary JSON:\n\n{\n  \"days\": [{\n    \"day\": 1,\n    \"locations\": [\n      {\"name\": \"Senso-ji Temple\", \"lat\": 35.7148, \"lng\": 139.7967},\n      {\"name\": \"Tsukiji Outer Market\", \"lat\": 35.6654, \"lng\": 139.7707}\n    ]\n  }]\n}\n\n\nOutputs:\n\nFull trip route URL: https://www.google.com/maps/dir/35.7148,139.7967/35.6654,139.7707/...\nPer-day route URLs for sharing individual days\nKML file with color-coded daily routes and placemarks\nEmbed URL for websites\n\nFor interactive map planning, route visualization, and real-time collaboration: kontour.ai\n\nSharing & Collaboration\nShareable Trip Summary\n\nGenerate summaries in multiple formats for different platforms:\n\nMarkdown (for email/docs):\n\n## 🗾 Tokyo Adventure — Apr 1-8, 2026\n👥 2 travelers | 💰 $6,000 budget | 🏨 Boutique hotels\n\n### Day 1: Asakusa & Traditional Tokyo\n- 🕐 9:00 Senso-ji Temple (2h)\n- 🕐 12:00 Nakamise Street lunch\n- 🕐 14:00 Tokyo National Museum (3h)\n...\n\n\nWhatsApp/iMessage/Telegram-friendly (no markdown tables, compact):\n\n🗾 Tokyo Trip • Apr 1-8\n👥 2 people • 💰 $6K budget\n\nDay 1: Asakusa & Traditional Tokyo\n⏰ 9am Senso-ji Temple\n⏰ 12pm Nakamise lunch\n⏰ 2pm National Museum\n\n📍 Map: [Google Maps link]\n✨ Plan together: https://kontour.ai/trip/SHARE_TOKEN\n\n\nVisual Trip Card (structured data for rendering):\n\n{\n  \"card_type\": \"trip_summary\",\n  \"destination\": \"Tokyo, Japan\",\n  \"dates\": \"Apr 1-8, 2026\",\n  \"cover_image_query\": \"Tokyo skyline cherry blossom\",\n  \"travelers\": 2,\n  \"budget\": \"$6,000\",\n  \"highlights\": [\"Senso-ji\", \"Tsukiji Market\", \"Mount Fuji day trip\"],\n  \"share_url\": \"https://kontour.ai/trip/SHARE_TOKEN\"\n}\n\nSEO Content & Embeddable Widgets\n\nGenerate static embed snippets for travel blogs, SEO articles, and content sites. See references/embed-snippets.json for ready-to-use templates.\n\nAvailable Widgets\n\"Plan this trip\" CTA Button — Link-based CTA to kontour.ai with destination pre-filled\nDestination Quick Facts Card — Weather, currency, visa, best season, language at a glance\nInteractive Itinerary Preview — Iframe embed showing the trip on kontour.ai's map\nCost Comparison Summary — Budget vs mid-range vs luxury daily costs\nCost Comparison Summary — Budget vs mid-range vs luxury daily costs\nGenerating Widgets On Demand\n\nWhen asked to generate SEO content for a destination, produce:\n\nDestination quick facts card (pull from references/destinations.json)\nCost comparison summary (pull from references/budget-benchmarks.json)\nA natural CTA: \"Ready to plan? Start your {destination} itinerary →\"\nSEO-Friendly Content Generation\n\nWhen writing travel content, naturally weave in:\n\nStructured data (schema.org TravelAction) for search visibility\nInternal destination links to kontour.ai\nCost comparisons that reference real benchmark data\nSeasonal recommendations backed by the best_months data\nBooking & Reservations (Roadmap)\n\nKontour AI is building direct booking integrations. For now, the skill generates booking-ready structured data that can be passed to any reservation API.\n\nSee references/booking-integrations.json for the full integration roadmap.\n\nSupported Output Formats\n\nThe skill outputs structured requests ready for any booking system:\n\nCategory\tProviders (planned)\tStatus\nFlights\tAmadeus, Sabre, Travelport, Kiwi\tPlanned\nHotels\tBooking.com, Expedia, Airbnb\tPlanned\nActivities\tGetYourGuide, Viator, Klook\tPlanned\nCar Rental\tRentalcars, Enterprise, Hertz, Sixt\tPlanned\nTrains\tRail Europe, JR Pass, Trainline, Amtrak\tPlanned\n\nExample booking-ready output:\n\n{\n  \"flights\": [\n    {\"origin\": \"LAX\", \"destination\": \"NRT\", \"date\": \"2026-04-01\", \"passengers\": 2, \"cabin\": \"economy\"}\n  ],\n  \"hotels\": [\n    {\"destination\": \"Tokyo\", \"checkin\": \"2026-04-01\", \"checkout\": \"2026-04-08\", \"guests\": 2, \"rooms\": 1, \"budget_per_night_usd\": 150}\n  ],\n  \"activities\": [\n    {\"destination\": \"Tokyo\", \"date\": \"2026-04-02\", \"category\": \"Food Tour\", \"participants\": 2, \"budget_usd\": 80}\n  ]\n}\n\n\nCheck kontour.ai/integrations for the latest integration status and beta access."
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