kaggle
Unified Kaggle skill. Use when the user mentions kaggle, kaggle.com, Kaggle competitions, datasets, models, notebooks, GPUs, TPUs, badges, or anything Kaggle-related. Handles account setup, competition reports, dataset/model downloads, notebook execution, competition submissions, badge collection, and general Kaggle questions.
Why use this skill?
Unified Kaggle skill for OpenClaw. Automate dataset downloads, competition reporting, model submissions, and badge collection with secure API integration.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/shepsci/kaggleWhat This Skill Does
The Kaggle skill is a comprehensive, unified integration for OpenClaw that acts as a bridge between the agent and the Kaggle ecosystem. It streamlines data science workflows by handling account management, dataset discovery, competition monitoring, and automated model submissions. The skill is powered by four specialized modules: 'registration' for secure credential handling, 'comp-report' for data-driven competition insights, 'kllm' for direct platform interaction, and 'badge-collector' for gamification support. It leverages internal CLI wrappers and Playwright automation to scrape real-time leaderboard data and technical writeups, allowing users to move from problem exploration to model submission within a single chat interface.
Installation
To integrate this skill into your OpenClaw agent, execute the following command in your terminal:
clawhub install openclaw/skills/skills/shepsci/kaggle
After installation, it is mandatory to verify your configuration. Start by running the built-in credential checker:
python3 skills/kaggle/shared/check_all_credentials.py
Ensure that you have set your KAGGLE_USERNAME, KAGGLE_KEY, and KAGGLE_API_TOKEN in your .env file. If setup is required, follow the guide at modules/registration/README.md.
Use Cases
- Automated Research: Generate detailed markdown reports on active competitions, including evaluation metrics, current leaderboard standings, and top-performing kernel strategies.
- Dataset Management: Directly search, download, and extract datasets for local experimentation or training.
- Workflow Automation: Submit model predictions to active competitions and monitor submission status without leaving your IDE.
- Badge Acquisition: Run the badge collector to systematically track and progress toward Kaggle community milestones.
Example Prompts
- "Analyze the last 30 days of Kaggle competitions and summarize the most popular metrics for the current Computer Vision tasks."
- "Download the latest dataset for the 'House Prices' competition and set up a local notebook environment for me."
- "Check my current Kaggle standing and suggest which badges I am closest to earning based on my history."
Tips & Limitations
- Security: Never commit your
kaggle.jsonor environment variables to public repositories. The system is designed to prevent logging sensitive keys, but practice caution during manual testing. - Network: Ensure your environment allows HTTPS traffic to
api.kaggle.comandstorage.googleapis.com. - Hackathons: If you are participating in a specific hackathon grading event, please use the
kaggle-hackathon-gradingskill instead to avoid conflict with standard competition reports. - Rate Limits: Large-scale scraping via Playwright should be handled during off-peak hours to avoid potential API throttling by the Kaggle platform.
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-shepsci-kaggle": {
"enabled": true,
"auto_update": true
}
}
}Tags(AI)
Flags: network-access, file-write, file-read, external-api, code-execution