Overview
- Skill Key
- elevo11/weather-plus
- Author
- elevo11
- Source Repo
- openclaw/skills
- Version
- -
- Source Path
- skills/elevo11/weather-plus
- Latest Commit SHA
- fc03f0051931ff276ad1991cfdb4fc609530a6fa
Get current weather, multi-day forecasts, clothing index, and feels-like temperature. No API key required. Use when a user wants to: (1) Check current weather, (2) View multi-day forecasts, (3) Get clothing/dressing recommendations, (4) Check feels-like temperature and comfort index. Supports any city worldwide. Integrates SkillPay.me at 0.001 USDT/call.
Stars
0
Installs
0
Status
ACTIVE
Visibility
PUBLIC
直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 weather-plus 技能。 若已安装,则直接安装 weather-plus 技能。
# Weather Plus Weather, forecasts, clothing index & feels-like temperature. No API key needed. 0.001 USDT/call. ## Commands | Command | Script | Description | |:---|:---|:---| | **weather** | `scripts/weather.py` | Current weather + feels-like | | **forecast** | `scripts/forecast.py` | Multi-day forecast (up to 7 days) | | **clothing** | `scripts/clothing.py` | Clothing/dressing index + recommendations | | **billing** | `scripts/billing.py` | SkillPay charge/balance/payment | ## Workflow ``` 1. Billing: python3 scripts/billing.py --charge --user-id <id> 2. Weather: python3 scripts/weather.py --city "Beijing" 3. Forecast: python3 scripts/forecast.py --city "Shanghai" --days 5 4. Clothing: python3 scripts/clothing.py --city "Chengdu" ``` ## Examples ```bash # Current weather python3 scripts/weather.py --city "New York" python3 scripts/weather.py --city "成都" # Multi-day forecast python3 scripts/forecast.py --city "Tokyo" --days 7 # Clothing index python3 scripts/clothing.py --city "Beijing" python3 scripts/clothing.py --city "London" ``` ## Config | Env Var | Required | Description | |:---|:---:|:---| | `SKILLPAY_API_KEY` | Yes | SkillPay.me API key | ## References See `references/clothing-index.md` for dressing recommendation methodology.
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