Your agent can do more. Find the skill that makes it happen.
Find your next superpower If you are an agent, refer to our llms.txt for full access.Runs Python through inference.sh with libraries such as NumPy, Pandas, Matplotlib, Pillow, OpenCV, and browser automation tools. Supports data processing, web scraping, image and video work, 3D processing, PDF generation, and API calls.
Runs Python code through inference.sh with preinstalled data, browser, image, video, and 3D libraries. Supports analysis, web scraping, PDF generation, API calls, media processing, and automation scripts.
Runs Python through inference.sh with preinstalled libraries such as NumPy, Pandas, Matplotlib, Pillow, OpenCV, and browser automation tools. Supports data analysis, web scraping, image and video processing, 3D work, PDF generation, API calls, and scripts.
Provides an inference.sh execution environment with scientific, browser, image, video, and 3D libraries preinstalled. Supports API calls, PDF generation, data analysis, and automation scripts.
Runs Python through inference.sh with preinstalled libraries including NumPy, Pandas, Matplotlib, Pillow, OpenCV, and browser automation tools. Supports data processing, web scraping, media and 3D processing, PDF generation, API calls, and scripts.
Runs Python in a sandboxed inference.sh environment with libraries such as NumPy, Pandas, Matplotlib, Pillow, OpenCV, and Playwright. Supports data processing, web scraping, image and video manipulation, 3D processing, PDF generation, API calls, and automation scripts.
Runs Python in a sandboxed inference.sh environment with libraries such as NumPy, Pandas, Matplotlib, Pillow, OpenCV, and Playwright. Supports data processing, web scraping, image and video manipulation, 3D processing, PDF generation, API calls, and automation scripts.
Provides Python guidance on code organization, PEP 8, design patterns, refactoring, and tests. Covers async/await, decorators, context managers, and other Python idioms.
Generates a complete MCP server project in Python. Includes tools, resources, and project configuration.
Implement Python observability through logging, metric collection, and tracing. Supports diagnosing and debugging production systems.
Supports major Python package changes and architecture improvements. Focuses on restructuring code, reducing redundancy, maintaining consistency, and addressing technical debt.
Create distributable Python packages with proper project structure, setup.py/pyproject.toml, and publishing to PyPI. Use when packaging Python libraries, creating CLI tools, or distributing Python code.
Skills give your agent reusable instructions for a specific job. Pick one, read what it does, and bring it into your workflow.
A name only tells half the story. Search the full description and instructions to find the right fit.
Read the skill, visit its source, and see exactly what you’re adding to your agent.
Copy the install command from a skill page and run it in your project.
npx skillycli add owner/repo --skill name