{"slug":"maps","title":"maps","summary":"Geocode, POIs, routes, timezones via OpenStreetMap/OSRM.","platform":"Claude","tags":[],"authorName":"LLM Mart","authorSlug":"llm-mart","score":0,"source":"github","price":null,"verified":false,"createdAt":"2026-10-17T09:13:09.749737Z","repo":{"url":"https://github.com/invergent-ai/surogates","stars":28,"forks":1,"license":"AGPL-3.0","updatedAt":"2026-10-16T18:37:14Z"},"bodyHtml":"
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name: maps\ndescription: \"Geocode, POIs, routes, timezones via OpenStreetMap/OSRM.\"\nversion: 1.2.0\nauthor: Mibayy\nlicense: MIT

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Maps Skill

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Location intelligence using free, open data sources. 8 commands, 44 POI\ncategories, zero dependencies (Python stdlib only), no API key required.

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Data sources: OpenStreetMap/Nominatim, Overpass API, OSRM, TimeAPI.io.

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This skill supersedes the old find-nearby skill — all of find-nearby's\nfunctionality is covered by the nearby command below, with the same\n--near \"<place>\" shortcut and multi-category support.

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When to Use

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Prerequisites

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Python 3.8+ (stdlib only — no pip installs needed).

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Script path: ~/.surogate/skills/maps/scripts/maps_client.py

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Commands

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MAPS=~/.surogate/skills/maps/scripts/maps_client.py\n
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search — Geocode a place name

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python3 $MAPS search \"Eiffel Tower\"\npython3 $MAPS search \"1600 Pennsylvania Ave, Washington DC\"\n
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Returns: lat, lon, display name, type, bounding box, importance score.

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reverse — Coordinates to address

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python3 $MAPS reverse 48.8584 2.2945\n
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Returns: full address breakdown (street, city, state, country, postcode).

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nearby — Find places by category

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# By coordinates (from a Telegram location pin, for example)\npython3 $MAPS nearby 48.8584 2.2945 restaurant --limit 10\npython3 $MAPS nearby 40.7128 -74.0060 hospital --radius 2000\n\n# By address / city / zip / landmark — --near auto-geocodes\npython3 $MAPS nearby --near \"Times Square, New York\" --category cafe\npython3 $MAPS nearby --near \"90210\" --category pharmacy\n\n# Multiple categories merged into one query\npython3 $MAPS nearby --near \"downtown austin\" --category restaurant --category bar --limit 10\n
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46 categories: restaurant, cafe, bar, hospital, pharmacy, hotel, guest_house,\ncamp_site, supermarket, atm, gas_station, parking, museum, park, school,\nuniversity, bank, police, fire_station, library, airport, train_station,\nbus_stop, church, mosque, synagogue, dentist, doctor, cinema, theatre, gym,\nswimming_pool, post_office, convenience_store, bakery, bookshop, laundry,\ncar_wash, car_rental, bicycle_rental, taxi, veterinary, zoo, playground,\nstadium, nightclub.

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Each result includes: name, address, lat/lon, distance_m,\nmaps_url (clickable Google Maps link), directions_url (Google Maps\ndirections from the search point), and promoted tags when available —\ncuisine, hours (opening_hours), phone, website.

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distance — Travel distance and time

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python3 $MAPS distance \"Paris\" --to \"Lyon\"\npython3 $MAPS distance \"New York\" --to \"Boston\" --mode driving\npython3 $MAPS distance \"Big Ben\" --to \"Tower Bridge\" --mode walking\n
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Modes: driving (default), walking, cycling. Returns road distance, duration,\nand straight-line distance for comparison.

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directions — Turn-by-turn navigation

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python3 $MAPS directions \"Eiffel Tower\" --to \"Louvre Museum\" --mode walking\npython3 $MAPS directions \"JFK Airport\" --to \"Times Square\" --mode driving\n
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Returns numbered steps with instruction, distance, duration, road name, and\nmaneuver type (turn, depart, arrive, etc.).

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timezone — Timezone for coordinates

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python3 $MAPS timezone 48.8584 2.2945\npython3 $MAPS timezone 35.6762 139.6503\n
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Returns timezone name, UTC offset, and current local time.

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area — Bounding box and area for a place

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python3 $MAPS area \"Manhattan, New York\"\npython3 $MAPS area \"London\"\n
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Returns bounding box coordinates, width/height in km, and approximate area.\nUseful as input for the bbox command.

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bbox — Search within a bounding box

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python3 $MAPS bbox 40.75 -74.00 40.77 -73.98 restaurant --limit 20\n
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Finds POIs within a geographic rectangle. Use area first to get the\nbounding box coordinates for a named place.

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Working With Telegram Location Pins

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When a user sends a location pin, the message contains latitude: and\nlongitude: fields. Extract those and pass them straight to nearby:

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# User sent a pin at 36.17, -115.14 and asked \"find cafes nearby\"\npython3 $MAPS nearby 36.17 -115.14 cafe --radius 1500\n
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Present results as a numbered list with names, distances, and the\nmaps_url field so the user gets a tap-to-open link in chat. For \"open\nnow?\" questions, check the hours field; if missing or unclear, verify\nwith web_search since OSM hours are community-maintained and not always\ncurrent.

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Workflow Examples

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\"Find Italian restaurants near the Colosseum\":

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  1. nearby --near \"Colosseum Rome\" --category restaurant --radius 500\n— one command, auto-geocoded
    2. \n
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\"What's near this location pin they sent?\":

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  1. Extract lat/lon from the Telegram message
    2. \n
  2. nearby LAT LON cafe --radius 1500
    3. \n
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\"How do I walk from hotel to conference center?\":

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  1. directions \"Hotel Name\" --to \"Conference Center\" --mode walking
    2. \n
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\"What restaurants are in downtown Seattle?\":

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  1. area \"Downtown Seattle\" → get bounding box
    2. \n
  2. bbox S W N E restaurant --limit 30
    3. \n
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Pitfalls

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Verification

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python3 ~/.surogate/skills/maps/scripts/maps_client.py search \"Statue of Liberty\"\n# Should return lat ~40.689, lon ~-74.044\n\npython3 ~/.surogate/skills/maps/scripts/maps_client.py nearby --near \"Times Square\" --category restaurant --limit 3\n# Should return a list of restaurants within ~500m of Times Square\n
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