Agent Skills › wukongrobot/wukongbot › local-places

local-places

GitHub

通过本地Google Places API代理搜索附近地点，支持位置解析、多条件筛选及详情查询，引导用户完成从模糊定位到精准推荐的交互流程。

skills/local-places/SKILL.md wukongrobot/wukongbot

Trigger Scenarios

查找附近的餐厅或咖啡馆根据偏好筛选地点

Install

npx skills add wukongrobot/wukongbot --skill local-places -g -y

More Options

Use without installing

npx skills use wukongrobot/wukongbot@local-places

指定 Agent (Claude Code)

npx skills add wukongrobot/wukongbot --skill local-places -a claude-code -g -y

安装 repo 全部 skill

npx skills add wukongrobot/wukongbot --all -g -y

预览 repo 内 skill

npx skills add wukongrobot/wukongbot --list

SKILL.md

Frontmatter

{
    "name": "local-places",
    "homepage": "https:\/\/github.com\/Hyaxia\/local_places",
    "metadata": {
        "moltbot": {
            "emoji": "📍",
            "requires": {
                "env": [
                    "GOOGLE_PLACES_API_KEY"
                ],
                "bins": [
                    "uv"
                ]
            },
            "primaryEnv": "GOOGLE_PLACES_API_KEY"
        }
    },
    "description": "Search for places (restaurants, cafes, etc.) via Google Places API proxy on localhost."
}

📍 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

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

Check server: curl http://127.0.0.1:8000/ping
Resolve location:

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

Search places:

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
  }'

Get details:

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

Conversation Flow

If user says "near me" or gives vague location → resolve it first
If multiple results → show numbered list, ask user to pick
Ask for preferences: type, open now, rating, price level
Search with location_bias from chosen location
Present results with name, rating, address, open status
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

{
  "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.