maps
Geocode, POIs, routes, timezones via OpenStreetMap/OSRM.
Best use case
maps is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Geocode, POIs, routes, timezones via OpenStreetMap/OSRM.
Teams using maps should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/maps/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How maps Compares
| Feature / Agent | maps | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Geocode, POIs, routes, timezones via OpenStreetMap/OSRM.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Maps Skill Location intelligence using free, open data sources. 8 commands, 44 POI categories, zero dependencies (Python stdlib only), no API key required. Data sources: OpenStreetMap/Nominatim, Overpass API, OSRM, TimeAPI.io. This skill supersedes the old `find-nearby` skill — all of find-nearby's functionality is covered by the `nearby` command below, with the same `--near "<place>"` shortcut and multi-category support. ## When to Use - User sends a Telegram location pin (latitude/longitude in the message) → `nearby` - User wants coordinates for a place name → `search` - User has coordinates and wants the address → `reverse` - User asks for nearby restaurants, hospitals, pharmacies, hotels, etc. → `nearby` - User wants driving/walking/cycling distance or travel time → `distance` - User wants turn-by-turn directions between two places → `directions` - User wants timezone information for a location → `timezone` - User wants to search for POIs within a geographic area → `area` + `bbox` ## Prerequisites Python 3.8+ (stdlib only — no pip installs needed). Script path: `~/.hermes/skills/maps/scripts/maps_client.py` ## Commands ```bash MAPS=~/.hermes/skills/maps/scripts/maps_client.py ``` ### search — Geocode a place name ```bash python3 $MAPS search "Eiffel Tower" python3 $MAPS search "1600 Pennsylvania Ave, Washington DC" ``` Returns: lat, lon, display name, type, bounding box, importance score. ### reverse — Coordinates to address ```bash python3 $MAPS reverse 48.8584 2.2945 ``` Returns: full address breakdown (street, city, state, country, postcode). ### nearby — Find places by category ```bash # By coordinates (from a Telegram location pin, for example) python3 $MAPS nearby 48.8584 2.2945 restaurant --limit 10 python3 $MAPS nearby 40.7128 -74.0060 hospital --radius 2000 # By address / city / zip / landmark — --near auto-geocodes python3 $MAPS nearby --near "Times Square, New York" --category cafe python3 $MAPS nearby --near "90210" --category pharmacy # Multiple categories merged into one query python3 $MAPS nearby --near "downtown austin" --category restaurant --category bar --limit 10 ``` 46 categories: restaurant, cafe, bar, hospital, pharmacy, hotel, guest_house, camp_site, supermarket, atm, gas_station, parking, museum, park, school, university, bank, police, fire_station, library, airport, train_station, bus_stop, church, mosque, synagogue, dentist, doctor, cinema, theatre, gym, swimming_pool, post_office, convenience_store, bakery, bookshop, laundry, car_wash, car_rental, bicycle_rental, taxi, veterinary, zoo, playground, stadium, nightclub. Each result includes: `name`, `address`, `lat`/`lon`, `distance_m`, `maps_url` (clickable Google Maps link), `directions_url` (Google Maps directions from the search point), and promoted tags when available — `cuisine`, `hours` (opening_hours), `phone`, `website`. ### distance — Travel distance and time ```bash python3 $MAPS distance "Paris" --to "Lyon" python3 $MAPS distance "New York" --to "Boston" --mode driving python3 $MAPS distance "Big Ben" --to "Tower Bridge" --mode walking ``` Modes: driving (default), walking, cycling. Returns road distance, duration, and straight-line distance for comparison. ### directions — Turn-by-turn navigation ```bash python3 $MAPS directions "Eiffel Tower" --to "Louvre Museum" --mode walking python3 $MAPS directions "JFK Airport" --to "Times Square" --mode driving ``` Returns numbered steps with instruction, distance, duration, road name, and maneuver type (turn, depart, arrive, etc.). ### timezone — Timezone for coordinates ```bash python3 $MAPS timezone 48.8584 2.2945 python3 $MAPS timezone 35.6762 139.6503 ``` Returns timezone name, UTC offset, and current local time. ### area — Bounding box and area for a place ```bash python3 $MAPS area "Manhattan, New York" python3 $MAPS area "London" ``` Returns bounding box coordinates, width/height in km, and approximate area. Useful as input for the bbox command. ### bbox — Search within a bounding box ```bash python3 $MAPS bbox 40.75 -74.00 40.77 -73.98 restaurant --limit 20 ``` Finds POIs within a geographic rectangle. Use `area` first to get the bounding box coordinates for a named place. ## Working With Telegram Location Pins When a user sends a location pin, the message contains `latitude:` and `longitude:` fields. Extract those and pass them straight to `nearby`: ```bash # User sent a pin at 36.17, -115.14 and asked "find cafes nearby" python3 $MAPS nearby 36.17 -115.14 cafe --radius 1500 ``` Present results as a numbered list with names, distances, and the `maps_url` field so the user gets a tap-to-open link in chat. For "open now?" questions, check the `hours` field; if missing or unclear, verify with `web_search` since OSM hours are community-maintained and not always current. ## Workflow Examples **"Find Italian restaurants near the Colosseum":** 1. `nearby --near "Colosseum Rome" --category restaurant --radius 500` — one command, auto-geocoded **"What's near this location pin they sent?":** 1. Extract lat/lon from the Telegram message 2. `nearby LAT LON cafe --radius 1500` **"How do I walk from hotel to conference center?":** 1. `directions "Hotel Name" --to "Conference Center" --mode walking` **"What restaurants are in downtown Seattle?":** 1. `area "Downtown Seattle"` → get bounding box 2. `bbox S W N E restaurant --limit 30` ## Pitfalls - Nominatim ToS: max 1 req/s (handled automatically by the script) - `nearby` requires lat/lon OR `--near "<address>"` — one of the two is needed - OSRM routing coverage is best for Europe and North America - Overpass API can be slow during peak hours; the script automatically falls back between mirrors (overpass-api.de → overpass.kumi.systems) - `distance` and `directions` use `--to` flag for the destination (not positional) - If a zip code alone gives ambiguous results globally, include country/state ## Verification ```bash python3 ~/.hermes/skills/maps/scripts/maps_client.py search "Statue of Liberty" # Should return lat ~40.689, lon ~-74.044 python3 ~/.hermes/skills/maps/scripts/maps_client.py nearby --near "Times Square" --category restaurant --limit 3 # Should return a list of restaurants within ~500m of Times Square ```
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