What makes Kontour Travel Planner notable?

5.4K downloads. Trust evidence available

How should Kontour Travel Planner be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

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agentCLAWHUBUnverified

Kontour Travel Planner

Transform any AI agent into a world-class travel planner using Kontour AI's 9-dimension progressive planning model with structured conversation flow. Skill: Kontour Travel Planner Owner: skylinehk Summary: Transform any AI agent into a world-class travel planner using Kontour AI's 9-dimension progressive planning model with structured conversation flow. Tags: itinerary:2.0.3, latest:2.0.43, offline:2.0.3, planning:2.0.3, travel:2.0.3 Version history: v2.0.43 | 2026-09-22T10:41:52.022Z | user Add post-nudge hold packet so operators wait after one reminder instead o

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

5.4k

Updated

Oct 9, 2026

Version

2.0.43

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 5.4K downloads reported by the source. Last updated 10/9/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 9, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 9, 2026
Adoption signal: 5.4K downloadsadoption · observed Oct 9, 2026
Latest release: 2.0.43release · observed Sep 22, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s172w5phb33spv0zh9b324d7g583egdn:travel-planner-notion-ai-obsidian-kontour-integration

Setup complexity is classified as HIGH. You must provision dedicated cloud infrastructure or an isolated VM. Do not run this directly on your local workstation.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-skylinehk-travel-planner-notion-ai-obsidian-kontour-int/snapshot"

Documentation

CLAWHUB

154,342 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: kontour-travel-planner
description: Transform any AI agent into a world-class travel planner using Kontour AI's 9-dimension progressive planning model with structured conversation flow.
version: 2.0.43
license: MIT-0
metadata:
  openclaw:
    emoji: "🧭"
    requires:
      env: []
      bins:
        - bash
        - python3
---

# Kontour Travel Planner

> The planning brain that any AI agent can plug in. Not a search wrapper — a planning **methodology**.

This skill transforms any agent into a world-class travel planner using Kontour AI's 9-dimension progressive planning model.

## Requirements

**No API keys or credentials required.** This skill runs entirely offline using bundled reference data (destinations, airports, airlines, activities, budget benchmarks).

- **Scripts** (`plan.sh`, `export-gmaps.sh`) — Pure local processing. No external API calls. Generates Google Maps URLs as plain links (no API key needed).
- **Reference data** (`references/`) — Static JSON files bundled with the skill.
- **`embed-snippets.json`** — Optional static marketing templates. These are informational only, do not load remote code, and are not required for planning functionality.
- **`booking-integrations.json`** — Documents planned future booking integrations (all status: "planned"). No active API connections.

### Security Transparency (for skill marketplaces)

To reduce false-positive trust flags and improve reviewer confidence:

- Runtime network behavior: `plan.sh` and `export-gmaps.sh` make **no outbound HTTP/API calls**.
- Credentials required: **none** (no API keys, tokens, OAuth, or env secrets).
- Declared runtime dependencies in frontmatter: `bash`, `python3` only.
- Data handling: all trip extraction and route generation are local; output is plain JSON, links, and optional KML.
- External CTA examples are informational only and not required for core planning.

Quick local verification:

```bash
# Should return no matches for network clients used by runtime scripts
rg -n "python3 -c|eval\(|exec\(|os\.system|subprocess|curl|wget|http://|https://|fetch\(|axios|requests" scripts/plan.sh scripts/export-gmaps.sh

# Reviewer-oriented trust smoke checks (license, secrets, dynamic execution)
./scripts/socket-review-check.sh
```

## How It Works

### 9-Dimension Planning Model

Every trip is tracked across 9 weighted dimensions:

| Dimension | Weight | What to Extract |
|-----------|--------|----------------|
| **Dates** | 20 | Specific dates, flexible windows, "next month", seasons |
| **Destination** | 15 | City, country, region, multi-city routes |
| **Budget** | 15 | Dollar range, tier (budget/mid/luxury), per-person vs total |
| **Duration** | 10 | Number of days, weekend vs week-long |
| **Travelers** | 10 | Count, adults/children/seniors, solo/couple/family/group |
| **Interests** | 10 | Activities, themes (adventure, food, culture, relaxation) |
| **Accommodation** | 10 | Hotel, hostel, Airbnb, resort, boutique |
| **Transport** | 5 | Fligh

README.md

# kontour-travel-planner

AI agent skill for world-class travel planning using a 9-dimension progressive planning model.

## Install

```bash
npx skills add kontour-travel-planner
```

Or browse on a supported skill marketplace.

## What This Skill Does

Transforms any AI agent into a travel planning consultant using a structured methodology:

- **9 weighted dimensions** — dates, destination, budget, duration, travelers, interests, accommodation, transport, constraints
- **4-stage conversation flow** — Discover → Develop → Refine → Confirm
- **Guided discovery** — one high-impact question per turn, concrete options, conflict detection
- **Structured output** — trip context JSON, candidate scoring explanations, output polish with owner-tagged next actions, day-by-day itinerary, budget breakdown, Google Maps export
- **Reference data** — 200 destinations, 500 airports, airlines, activities, budget benchmarks (no API needed)

## Reference Data

Ground truth files in `references/`:

| File | Contents |
|------|----------|
| `destinations.json` | 200 global destinations with coordinates, costs, best months |
| `airports.json` | 500 airports with IATA codes and coordinates |
| `airlines.json` | Major airlines with alliances, hubs, regions |
| `activities.json` | Activity types with durations, cost tiers |
| `budget-benchmarks.json` | Daily cost benchmarks by destination tier |
| `booking-integrations.json` | Integration roadmap for booking providers |
| `embed-snippets.json` | Optional static CTA/template examples |

## Constraint Capture Smoke Test

The planner extracts operator-visible constraint details from natural-language requests, including budget caps, trip pace, neighborhood/base preference, opening-hours sensitivity, food preference, and weather sensitivity. Run the offline regression check with:

```bash
./scripts/test-plan-constraints.sh
```

## Candidate Scoring Explanations

When the request includes a known destination, `scripts/plan.sh` now emits `suggested_places` with ranked highlights and concise `why_chosen` factors. Each explanation references at least two concrete scoring factors such as destination fit, thematic fit, budget fit, hours sensitivity, or weather screening, so operators can see why a place entered the first-pass plan.

## Day-Plan Continuity

For known destinations with enough ranked highlights, `scripts/plan.sh` emits `day_plan_continuity`: a morning/afternoon/evening sequencing scaffold with zones, continuity reasons, and transition rationale. This gives operators a compact first pass that reduces avoidable backtracking before a full itinerary or route export is finalized.

## Risk + Fallback Warnings

When constraints make a first-pass plan fragile, `scripts/plan.sh` emits `risk_fallbacks` instead of failing bluntly. The warnings currently cover closed-venue/opening-hours risk, weather mismatch, sparse-area destinations outside bundled references, and over-constrained budget caps, with each warning naming the neare

_meta.json

{
  "ownerId": "kn78yww77gm7hxwgx0jewrmag981vb1p",
  "slug": "travel-planner-notion-ai-obsidian-kontour-integration",
  "version": "2.0.43",
  "publishedAt": 1790073712022
}

references/activities.json

[
  {"category": "Museum/Gallery", "typical_duration_hours": 2.5, "cost_tier": "budget", "best_for": ["solo", "couple", "family"], "indoor_outdoor": "indoor"},
  {"category": "Historical Site", "typical_duration_hours": 2, "cost_tier": "budget", "best_for": ["solo", "couple", "family", "group"], "indoor_outdoor": "outdoor"},
  {"category": "City Walking Tour", "typical_duration_hours": 3, "cost_tier": "budget", "best_for": ["solo", "couple", "group"], "indoor_outdoor": "outdoor"},
  {"category": "Food Tour", "typical_duration_hours": 3.5, "cost_tier": "mid", "best_for": ["solo", "couple", "group"], "indoor_outdoor": "both"},
  {"category": "Cooking Class", "typical_duration_hours": 3, "cost_tier": "mid", "best_for": ["solo", "couple", "group"], "indoor_outdoor": "indoor"},
  {"category": "Wine/Beer Tasting", "typical_duration_hours": 2, "cost_tier": "mid", "best_for": ["couple", "group"], "indoor_outdoor": "indoor"},
  {"category": "Snorkeling", "typical_duration_hours": 3, "cost_tier": "mid", "best_for": ["solo", "couple", "family"], "indoor_outdoor": "outdoor"},
  {"category": "Scuba Diving", "typical_duration_hours": 4, "cost_tier": "luxury", "best_for": ["solo", "couple"], "indoor_outdoor": "outdoor"},
  {"category": "Hiking/Trekking", "typical_duration_hours": 5, "cost_tier": "budget", "best_for": ["solo", "couple", "group"], "indoor_outdoor": "outdoor"},
  {"category": "Beach Day", "typical_duration_hours": 5, "cost_tier": "budget", "best_for": ["solo", "couple", "family", "group"], "indoor_outdoor": "outdoor"},
  {"category": "Surfing Lesson", "typical_duration_hours": 2, "cost_tier": "mid", "best_for": ["solo", "couple"], "indoor_outdoor": "outdoor"},
  {"category": "Zip-lining", "typical_duration_hours": 2, "cost_tier": "mid", "best_for": ["couple", "family", "group"], "indoor_outdoor": "outdoor"},
  {"category": "Rock Climbing", "typical_duration_hours": 3, "cost_tier": "mid", "best_for": ["solo", "couple", "group"], "indoor_outdoor": "outdoor"},
  {"category": "Kayaking/Canoeing", "typical_duration_hours": 3, "cost_tier": "mid", "best_for": ["solo", "couple", "family"], "indoor_outdoor": "outdoor"},
  {"category": "Safari/Wildlife Tour", "typical_duration_hours": 8, "cost_tier": "luxury", "best_for": ["couple", "family", "group"], "indoor_outdoor": "outdoor"},
  {"category": "Hot Air Balloon", "typical_duration_hours": 1.5, "cost_tier": "luxury", "best_for": ["couple"], "indoor_outdoor": "outdoor"},
  {"category": "Spa/Wellness", "typical_duration_hours": 3, "cost_tier": "luxury", "best_for": ["solo", "couple"], "indoor_outdoor": "indoor"},
  {"category": "Theme Park", "typical_duration_hours": 8, "cost_tier": "mid", "best_for": ["family", "group", "couple"], "indoor_outdoor": "outdoor"},
  {"category": "Nightlife/Bar Hopping", "typical_duration_hours": 4, "cost_tier": "mid", "best_for": ["solo", "couple", "group"], "indoor_outdoor": "indoor"},
  {"category": "Theater/Show", "typical_duration_hours": 2.5, "cost_tier": "mid", "best_for"

references/airlines.json

[
  {"name": "American Airlines", "iata": "AA", "alliance": "oneworld", "hubs": ["DFW", "CLT", "MIA", "PHL", "ORD"], "regions": ["North America", "Europe", "Latin America", "Asia"]},
  {"name": "Delta Air Lines", "iata": "DL", "alliance": "SkyTeam", "hubs": ["ATL", "MSP", "DTW", "SLC", "SEA", "JFK", "LAX", "BOS"], "regions": ["North America", "Europe", "Asia", "Latin America"]},
  {"name": "United Airlines", "iata": "UA", "alliance": "Star Alliance", "hubs": ["ORD", "EWR", "IAH", "DEN", "SFO", "LAX", "IAD"], "regions": ["North America", "Europe", "Asia", "Latin America", "Oceania"]},
  {"name": "Southwest Airlines", "iata": "WN", "alliance": null, "hubs": ["DAL", "MDW", "BWI", "DEN", "LAS", "PHX"], "regions": ["North America"]},
  {"name": "JetBlue Airways", "iata": "B6", "alliance": null, "hubs": ["JFK", "BOS", "FLL", "MCO"], "regions": ["North America", "Caribbean"]},
  {"name": "Alaska Airlines", "iata": "AS", "alliance": "oneworld", "hubs": ["SEA", "SFO", "LAX", "PDX"], "regions": ["North America"]},
  {"name": "Air Canada", "iata": "AC", "alliance": "Star Alliance", "hubs": ["YYZ", "YVR", "YUL"], "regions": ["North America", "Europe", "Asia"]},
  {"name": "British Airways", "iata": "BA", "alliance": "oneworld", "hubs": ["LHR", "LGW"], "regions": ["Europe", "North America", "Asia", "Africa"]},
  {"name": "Lufthansa", "iata": "LH", "alliance": "Star Alliance", "hubs": ["FRA", "MUC"], "regions": ["Europe", "North America", "Asia", "Africa"]},
  {"name": "Air France", "iata": "AF", "alliance": "SkyTeam", "hubs": ["CDG", "ORY"], "regions": ["Europe", "North America", "Africa", "Asia"]},
  {"name": "KLM", "iata": "KL", "alliance": "SkyTeam", "hubs": ["AMS"], "regions": ["Europe", "North America", "Asia", "Africa"]},
  {"name": "Emirates", "iata": "EK", "alliance": null, "hubs": ["DXB"], "regions": ["Middle East", "Europe", "Asia", "Africa", "North America", "Oceania"]},
  {"name": "Qatar Airways", "iata": "QR", "alliance": "oneworld", "hubs": ["DOH"], "regions": ["Middle East", "Europe", "Asia", "Africa", "North America", "Oceania"]},
  {"name": "Etihad Airways", "iata": "EY", "alliance": null, "hubs": ["AUH"], "regions": ["Middle East", "Europe", "Asia", "Africa", "Oceania"]},
  {"name": "Turkish Airlines", "iata": "TK", "alliance": "Star Alliance", "hubs": ["IST"], "regions": ["Europe", "Asia", "Africa", "Middle East", "North America"]},
  {"name": "Singapore Airlines", "iata": "SQ", "alliance": "Star Alliance", "hubs": ["SIN"], "regions": ["Asia", "Europe", "Oceania", "North America"]},
  {"name": "Cathay Pacific", "iata": "CX", "alliance": "oneworld", "hubs": ["HKG"], "regions": ["Asia", "Europe", "North America", "Oceania"]},
  {"name": "Japan Airlines", "iata": "JL", "alliance": "oneworld", "hubs": ["NRT", "HND"], "regions": ["Asia", "North America", "Europe"]},
  {"name": "ANA", "iata": "NH", "alliance": "Star Alliance", "hubs": ["NRT", "HND"], "regions": ["Asia", "North America", "Europe"]},
  {"name": "Korean Air", "iata": "KE", "alliance

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