# Local Places

> Searches for local businesses and points of interest via a Google Places API proxy running on localhost. Resolves vague locations, applies filters for type, rating, and price, and returns structured place details. Use when the user asks to find restaurants, nearby places, coffee shops, business search, local recommendations, or anything involving place discovery by location. Use when this capability is needed.

- Skill: `tomevault-io/local-places` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add tomevault-io/local-places`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/local-places/raw
- Safety review: pending (external: skill-scanner PASS, skillspector CAUTION)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Product & Planning
- Author: tomevault-io (https://skillmd.com/u/tomevault-io)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tomevault-io/local-places

---


# 📍 Local Places

_Find places, Go fast_

Search for nearby places using a local Google Places API proxy. Two-step flow: resolve location first, then search.

## Setup

```bash
cd {baseDir}
echo "GOOGLE_PLACES_API_KEY=your-key" > .env
uv venv && uv pip install -e ".[dev]"
uv run --env-file .env uvicorn local_places.main:app --host 127.0.0.1 --port 8000
```

Requires `GOOGLE_PLACES_API_KEY` in `.env` or environment.

## Quick Start

1. **Check server:** `curl http://127.0.0.1:8000/ping`

2. **Resolve location:**

```bash
curl -X POST http://127.0.0.1:8000/locations/resolve \
  -H "Content-Type: application/json" \
  -d '{"location_text": "Soho, London", "limit": 5}'
```

3. **Search places:**

```bash
curl -X POST http://127.0.0.1:8000/places/search \
  -H "Content-Type: application/json" \
  -d '{
    "query": "coffee shop",
    "location_bias": {"lat": 51.5137, "lng": -0.1366, "radius_m": 1000},
    "filters": {"open_now": true, "min_rating": 4.0},
    "limit": 10
  }'
```

4. **Get details:**

```bash
curl http://127.0.0.1:8000/places/{place_id}
```

## Conversation Flow

1. If user says "near me" or gives vague location → resolve it first
2. If multiple results → show numbered list, ask user to pick
3. Ask for preferences: type, open now, rating, price level
4. Search with `location_bias` from chosen location
5. Present results with name, rating, address, open status
6. Offer to fetch details or refine search

## Filter Constraints

- `filters.types`: exactly ONE type (e.g., "restaurant", "cafe", "gym")
- `filters.price_levels`: integers 0-4 (0=free, 4=very expensive)
- `filters.min_rating`: 0-5 in 0.5 increments
- `filters.open_now`: boolean
- `limit`: 1-20 for search, 1-10 for resolve
- `location_bias.radius_m`: must be > 0

## Response Format

```json
{
  "results": [
    {
      "place_id": "ChIJ...",
      "name": "Coffee Shop",
      "address": "123 Main St",
      "location": { "lat": 51.5, "lng": -0.1 },
      "rating": 4.6,
      "price_level": 2,
      "types": ["cafe", "food"],
      "open_now": true
    }
  ],
  "next_page_token": "..."
}
```

Use `next_page_token` as `page_token` in next request for more results.

---
> Converted and distributed by [TomeVault](https://tomevault.io/claim/elizaos) — claim your Tome and manage your conversions.
<!-- tomevault:4.0:skill_md:2026-04-11 -->