What problem does it solve? Building multiple Agno agents for study often leads to tangled dependencies, shared environments, and inconsistent structure. This Skill provides a master guide for organizing a study workspace where each agent is fully isolated, reproducible, and documented. ## Core Features & Use Cases - Isolated Agent Projects: Each agent lives in its own directory with a dedicated pyproject.toml and virtual environment managed by uv, with no shared dependencies between agents. - Level-Based Progression Map: Routes each concept (tools, RAG, memory, teams, workflows, AgentOS, AWS deploy) to the corresponding specialized skill, from basic agents to serverless deployment. - Cross-Cutting Best Practices: Enforces guardrails on every agent, environment-variable-based provider configuration, pinned dependency versions, and per-agent README documentation. - Use Case: When asked to create a new study agent for RAG, the Skill directs creating agents/rag-demo/, setting up uv isolation, implementing with the agno-knowledge-rag skill, and validating locally. ## Quick Start Ask the assistant to create a new isolated Agno study agent for a specific concept such as tools, RAG, or teams, following this master guide.
