Skill ディレクトリ

AI Agent のための再利用可能な Skill を見つける。

タスクで実際の GitHub Skill を検索し、利用前に Stars、Trust、監査、カテゴリ、インストール経路を確認できます。

すべての推奨は、リポジトリ、監査、インストール経路に明確につながっています。

検索結果: weather-radars

英語版ディレクトリ

Beautiful, hand-crafted animated weather icons that feel alive.

1.6K
Stars
76/100
信頼
カテゴリ: design-creative監査

Personal Assistant built using python libraries. It does almost anything which includes sending emails, Optical Text Recognition, Dynamic News Reporting at any time with API integration, Todo list generator, Opens any website with just a voice command, Plays Music, Wikipedia searching, Dictionary with Intelligent Sensing i.e. auto spell checking, Weather Reporting i.e. temp, wind speed, humidity, YouTube searching, Google Map searching, Youtube Downloading, etc.

1.3K
Stars
73/100
信頼
カテゴリ: media-automation監査

The Python-ARM Radar Toolkit. A data model driven interactive toolkit for working with weather radar data.

595
Stars
70/100
信頼
カテゴリ: data-analysis監査

☁️ ❄️ A KMP weather app built with Jetpack Compose , MVI , Unit Testing , Hilt and Location Services, Github Actions, Firebase + Material 3

188
Stars
70/100
信頼
カテゴリ: design-creative監査

Bresser 5-in-1/6-in-1/7-in-1 868 MHz Weather Sensor Radio Receiver for Arduino based on CC1101, SX1276/RFM95W, SX1262 or LR1121

179
Stars
70/100
信頼
カテゴリ: robotics-iot監査

Multi-platform prediction market trading bot: trades weather temperature markets on Kalshi (KXHIGH series) and Polymarket using 31-member GFS ensemble forecasts + BTC 5-min microstructure signals. Kelly criterion sizing, signal calibration, React dashboard. (Highest profits $1.8k)

441
Stars
66/100
信頼
カテゴリ: finance監査

Generate automated daily progress reports from site data. Track work completed, labor hours, equipment usage, and weather conditions.

282
Stars
64/100
信頼
カテゴリ: design-creative監査

Analyze labor productivity from site data. Compare planned vs actual, identify trends, benchmark against industry standards.

282
Stars
63/100
信頼
カテゴリ: data-analysis監査

QGIS toolkit 🧰 for pre- and post-processing 🔨, visualizing 🔍, and running simulations 💻 in the Weather Research and Forecasting (WRF) model 🌀

185
Stars
62/100
信頼
カテゴリ: geo-science監査

Rain Rendering for Evaluating and Improving Robustness to Bad Weather (Tremblay et al., 2020) (S. S. Halder et al., 2019)

170
Stars
61/100
信頼
カテゴリ: robotics-iot監査

Use when building AI agents with agentfootprint — LLMCall, Agent, skills, RAG, memory, control flow, Swarm concepts, mock/anthropic/openai/ollama providers, tools, recorders, resilience, and streaming. Also use when someone asks how agentfootprint works or wants to understand the framework.

20
Stars
61/100
信頼
カテゴリ: design-creative監査