# Find Nearby

> 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.

- Skill: `ichichuang/find-nearby` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds add ichichuang/find-nearby`
- Raw SKILL.md: https://api.skillmd.com/api/skills/ichichuang/find-nearby/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Integrations & APIs
- Author: ichichuang (https://skillmd.com/u/ichichuang)
- Updated: 2026-08-19
- Page: https://skillmd.com/skills/ichichuang/find-nearby

---


# 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