Find nearby places (restaurants, cafes, bars, pharmacies, etc.) using
Scanned 9/6/2026
Install to Claude Code
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---
description: Find nearby places (restaurants, cafes, bars, pharmacies, etc.) using
OpenStreetMap. Works with coordinates, addresses, cities, zip codes, or Telegram
location pins. No API keys needed.
version: 1.0.0
metadata:
catalog:
tags:
- location
- maps
- nearby
- places
- restaurants
- local
related_skills: []
---
## Kheish Compatibility
This skill is repo-local and stays inactive until explicitly activated.
When the original instructions refer to legacy tool names, use these Kheish mappings:
- `terminal` => `bash`
- `web_extract` => `web_fetch`, plus `web_search` when discovery is needed
- `search_files` => `grep_search` and `glob_search`
- `browser_*` tools require a browser-capable surfaced tool or MCP; if none is available, use the closest available surface and say so explicitly
When the instructions mention local helper files, resolve them from `${KHEISH_SKILL_DIR}`.
# Find Nearby — Local Place Discovery
Find restaurants, cafes, bars, pharmacies, and other places near any location. Uses OpenStreetMap (free, no API keys). Works with:
- **Coordinates** from Telegram location pins (latitude/longitude in conversation)
- **Addresses** ("near 123 Main St, Springfield")
- **Cities** ("restaurants in downtown Austin")
- **Zip codes** ("pharmacies near 90210")
- **Landmarks** ("cafes near Times Square")
## Quick Reference
```bash
# By coordinates (from Telegram location pin or user-provided)
python3 SKILL_DIR/scripts/find_nearby.py --lat <LAT> --lon <LON> --type restaurant --radius 1500
# By address, city, or landmark (auto-geocoded)
python3 SKILL_DIR/scripts/find_nearby.py --near "Times Square, New York" --type cafe
# Multiple place types
python3 SKILL_DIR/scripts/find_nearby.py --near "downtown austin" --type restaurant --type bar --limit 10
# JSON output
python3 SKILL_DIR/scripts/find_nearby.py --near "90210" --type pharmacy --json
```
### Parameters
| Flag | Description | Default |
|------|-------------|---------|
| `--lat`, `--lon` | Exact coordinates | — |
| `--near` | Address, city, zip, or landmark (geocoded) | — |
| `--type` | Place type (repeatable for multiple) | restaurant |
| `--radius` | Search radius in meters | 1500 |
| `--limit` | Max results | 15 |
| `--json` | Machine-readable JSON output | off |
### Common Place Types
`restaurant`, `cafe`, `bar`, `pub`, `fast_food`, `pharmacy`, `hospital`, `bank`, `atm`, `fuel`, `parking`, `supermarket`, `convenience`, `hotel`
## Workflow
1. **Get the location.** Look for coordinates (`latitude: ... / longitude: ...`) from a Telegram pin, or ask the user for an address/city/zip.
2. **Ask for preferences** (only if not already stated): place type, how far they're willing to go, any specifics (cuisine, "open now", etc.).
3. **Run the script** with appropriate flags. Use `--json` if you need to process results programmatically.
4. **Present results** with names, distances, and Google Maps links. If the user asked about hours or "open now," check the `hours` field in results — if missing or unclear, verify with `web_search`.
5. **For directions**, use the `directions_url` from results, or construct: `https://www.google.com/maps/dir/?api=1&origin=<LAT>,<LON>&destination=<LAT>,<LON>`
## Tips
- If results are sparse, widen the radius (1500 → 3000m)
- For "open now" requests: check the `hours` field in results, cross-reference with `web_search` for accuracy since OSM hours aren't always complete
- Zip codes alone can be ambiguous globally — prompt the user for country/state if results look wrong
- The script uses OpenStreetMap data which is community-maintained; coverage varies by region
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
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