local-places
Search for places (restaurants, cafes, etc.) via Google Places API proxy on localhost.
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install molt-bot-clawdbot-local-places
Repository
Skill path: skills/local-places
Search for places (restaurants, cafes, etc.) via Google Places API proxy on localhost.
Open repositoryBest for
Primary workflow: Ship Full Stack.
Technical facets: Full Stack, Backend.
Target audience: everyone.
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: molt-bot.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install local-places into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/molt-bot/clawdbot before adding local-places to shared team environments
- Use local-places for development workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.
Original source / Raw SKILL.md
---
name: local-places
description: Search for places (restaurants, cafes, etc.) via Google Places API proxy on localhost.
homepage: https://github.com/Hyaxia/local_places
metadata: {"clawdbot":{"emoji":"π","requires":{"bins":["uv"],"env":["GOOGLE_PLACES_API_KEY"]},"primaryEnv":"GOOGLE_PLACES_API_KEY"}}
---
# π 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 β resolve it first
2. If multiple results β 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.