local-places
Search for places (restaurants, cafes, etc.) via Google Places API proxy on localhost.
Best use case
local-places is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Search for places (restaurants, cafes, etc.) via Google Places API proxy on localhost.
Teams using local-places 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/local-places/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How local-places Compares
| Feature / Agent | local-places | 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?
Search for places (restaurants, cafes, etc.) via Google Places API proxy on localhost.
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
# 📍 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": "..."
}
```
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