Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
- Added curl and jq as required binaries in the skill metadata. - No other user-visible changes.
What This Skill Does
Wraps the Camino AI journey endpoint to plan day trips, walking tours, and multi-stop itineraries. Takes a list of coordinates with purposes and optional constraints like transport mode and time budget, then returns route segments, total distance, duration, and feasibility analysis.
Combining feasibility checking with route optimization in a single call avoids manually cross-referencing map tools and transit time calculators.
When to use it
- Planning a walking tour through multiple landmarks in a new city
- Checking if a day trip itinerary fits within a time limit
- Routing a business meeting circuit across downtown stops
- Building a cycling tour route with distance and time estimates
- Validating a road trip sequence before driving
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Plan a 4-hour walking tour of Paris starting at the Eiffel Tower, then the Louvre, then Notre-Dame
- 1Extracts waypoint coordinates and purposes for each landmark
- 2Sets transport mode to foot and time_budget to 4 hours
- 3Calls the Camino AI journey endpoint with the waypoints and constraints
- 4Parses route_segments for per-leg distance and duration
- 5Returns the feasibility result, total time, and any optimization suggestions
A structured itinerary showing each leg's distance and walk time, confirmation the tour fits within 4 hours, and a suggestion to reorder stops to reduce backtracking
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.