Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Google Maps integration for OpenClaw with Routes API. Use for: (1) Distance/travel time calculations with traffic prediction, (2) Turn-by-turn directions, (3...
Google Maps integration for OpenClaw with Routes API. Use for: (1) Distance/travel time calculations with traffic prediction, (2) Turn-by-turn directions, (3...
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
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.
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.
Google Maps integration powered by the Routes API.
GOOGLE_API_KEY environment variable Enable in Google Cloud Console: Routes API, Places API, Geocoding API
Env VariableDefaultDescriptionGOOGLE_API_KEY-Required. Your Google Maps API keyGOOGLE_MAPS_API_KEY-Alternative to GOOGLE_API_KEY (fallback)GOOGLE_MAPS_LANGenResponse language (en, he, ja, etc.) Set in OpenClaw config: { "env": { "GOOGLE_API_KEY": "AIza...", "GOOGLE_MAPS_LANG": "en" } }
python3 skills/google-maps/lib/map_helper.py <action> [options]
python3 lib/map_helper.py distance "origin" "destination" [options] Options: OptionValuesDescription--modedriving, walking, bicycling, transitTravel mode (default: driving)--departnow, +30m, +1h, 14:00, 2026-02-07 08:00Departure time--arrive14:00Arrival time (transit only)--trafficbest_guess, pessimistic, optimisticTraffic model--avoidtolls, highways, ferriesComma-separated Examples: python3 lib/map_helper.py distance "New York" "Boston" python3 lib/map_helper.py distance "Los Angeles" "San Francisco" --depart="+1h" python3 lib/map_helper.py distance "Chicago" "Detroit" --depart="08:00" --traffic=pessimistic python3 lib/map_helper.py distance "London" "Manchester" --mode=transit --arrive="09:00" python3 lib/map_helper.py distance "Paris" "Lyon" --avoid=tolls,highways Response: { "distance": "215.2 mi", "distance_meters": 346300, "duration": "3 hrs 45 mins", "duration_seconds": 13500, "static_duration": "3 hrs 30 mins", "duration_in_traffic": "3 hrs 45 mins" }
python3 lib/map_helper.py directions "origin" "destination" [options] Additional options (beyond distance): OptionDescription--alternativesReturn multiple routes--waypointsIntermediate stops (pipe-separated)--optimizeOptimize waypoint order (TSP) Examples: python3 lib/map_helper.py directions "New York" "Washington DC" python3 lib/map_helper.py directions "San Francisco" "Los Angeles" --alternatives python3 lib/map_helper.py directions "Miami" "Orlando" --waypoints="Fort Lauderdale|West Palm Beach" --optimize Response includes: summary, labels, duration, static_duration, warnings, steps[], optimized_waypoint_order
Calculate distances between multiple origins and destinations: python3 lib/map_helper.py matrix "orig1|orig2" "dest1|dest2" Example: python3 lib/map_helper.py matrix "New York|Boston" "Philadelphia|Washington DC" Response: { "origins": ["New York", "Boston"], "destinations": ["Philadelphia", "Washington DC"], "results": [ {"origin_index": 0, "destination_index": 0, "distance": "97 mi", "duration": "1 hr 45 mins"}, {"origin_index": 0, "destination_index": 1, "distance": "225 mi", "duration": "4 hrs 10 mins"} ] }
python3 lib/map_helper.py geocode "1600 Amphitheatre Parkway, Mountain View, CA" python3 lib/map_helper.py geocode "10 Downing Street, London"
python3 lib/map_helper.py reverse 40.7128 -74.0060 # New York City python3 lib/map_helper.py reverse 51.5074 -0.1278 # London
python3 lib/map_helper.py search "coffee near Times Square" python3 lib/map_helper.py search "pharmacy in San Francisco" --open
python3 lib/map_helper.py details "<place_id>"
ModelUse Casebest_guessDefault balanced estimatepessimisticImportant meetings (worst-case)optimisticBest-case scenario
Some features may not be available in all countries: FeatureAvailability--fuel-efficientUS, EU, select countries--shorterLimited availability--mode=two_wheelerAsia, select countries Check Google Maps coverage for details.
Works with addresses in any language: # Hebrew python3 lib/map_helper.py distance "ΧͺΧ ΧΧΧΧ" "ΧΧ¨ΧΧ©ΧΧΧ" python3 lib/map_helper.py geocode "ΧΧΧΧ ΧΧΧ£ 50, ΧͺΧ ΧΧΧΧ" # Japanese python3 lib/map_helper.py distance "ζ±δΊ¬" "ε€§ιͺ" # Arabic python3 lib/map_helper.py distance "Ψ―Ψ¨Ω" "Ψ£Ψ¨Ω ΨΈΨ¨Ω" Language configuration: Set default via env: GOOGLE_MAPS_LANG=he (persists) Override per-request: --lang=ja # Set Hebrew as default in OpenClaw config GOOGLE_MAPS_LANG=he # Override for specific request python3 lib/map_helper.py distance "Tokyo" "Osaka" --lang=ja
python3 lib/map_helper.py help
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