What problem does it solve? Setting up dependencies for multiple AI agents often leads to version conflicts and leaked API keys. This Skill standardizes the creation of isolated Python projects per agent, so each agent has its own virtual environment, pinned dependencies, and safely managed credentials. ## Core Features & Use Cases - Isolated Agent Projects: Creates one uv-managed Python project per agent so dependencies never interfere across agents. - Provider-Specific Dependencies: Installs only the packages each agent needs, such as openai, groq, ollama, lancedb, or the FastAPI extras for AgentOS. - Secure Secret Management: Defines .env and .env.example patterns with python-dotenv loading, plus .gitignore rules that keep keys out of version control. - Use Case: When starting a new Agno agent that calls the Groq API, use this Skill to scaffold the project, add only the groq dependency, pin versions with uv lock, and load the API key from a .env file. ## Quick Start Set up a new isolated Agno agent project named support-bot with uv, add the agno and groq dependencies, and create the .env.example file for API keys.
