kaggle-with-ai-template

Get competition metadata, data files, and rules using Kaggle MCP. Use when looking up competition details, searching competitions, or fetching competition data file info.

Search, download, and manage Kaggle datasets using Kaggle MCP. Use when finding datasets, checking file structures, or downloading data.

Browse and search Kaggle discussion forums using Kaggle MCP. Use when looking for tips, solutions, or community insights about competitions or datasets.

View and analyze competition leaderboard and submissions using Kaggle MCP. Use when checking rankings, scores, or submission history.

Search, view, save, and run Kaggle notebooks using Kaggle MCP. Use when exploring public notebooks, pushing code to Kaggle, or managing notebook sessions.

Submit to a Kaggle competition (code/notebook submission or file upload). Use when submitting predictions or notebooks to a competition.

Initialize project and set up competition environment (all-in-one). Use when starting a new Kaggle/atmaCup competition project or when user invokes /setup.

This skill downloads training results (model weights, training logs, metrics) from a vast.ai GPU instance to the local project. It should be used after remote training completes and BEFORE destroying the instance. Triggers include downloading results, fetching trained model, or collecting training artifacts from vast.ai.

This skill provisions a vast.ai GPU instance and syncs project code for remote training. It should be used when the user wants to train a model on a remote GPU via vast.ai, including instance creation, code sync, and SSH connection setup.

OpenAI Codex CLIを使用したコードレビュー、分析、コードベースへの質問を実行する。使用場面: (1) コードレビュー依頼時、(2) コードベース全体の分析、(3) 実装に関する質問、(4) バグの調査、(5) リファクタリング提案、(6) 解消が難しい問題の調査。トリガー: "codex", "コードレビュー", "レビューして", "分析して", "/codex"