akillness agno
Agno is a leading agent framework in the 2026 AI agent engineering landscape (41.0k★).
When to use this skill
- SDK for building agent platforms: agents, teams, workflows
- AgentOS: production runtime (FastAPI-based) with tracing, scheduling, RBAC and a control-plane UI
- Run agents from any framework under one control plane; own your data/context/tools/permissions
- Memory, storage, knowledge (vector DB integrations) built in
- Multimodal agents (text, image, audio, video)
- Human-review loops and pre-hooks/guardrails
- Ecosystem overlap: agent-system-design covers SLA discipline conceptually; agno is a concrete platform implementing those controls
Installation
pip install agno
Core API
from agno.agent import Agent
from agno.models.openai import OpenAIChat
agent = Agent(model=OpenAIChat(id="gpt-5"), tools=[], markdown=True)
agent.print_response("Share a 2 sentence horror story")
# platform: agno.os AgentOS app -> serve with FastAPI
Instructions
Step 1: Initialize the environment
Verify you have Python installed and set up properly. Use the correct package manager (pip, npm, pnpm, uv) as specified in the installation section.
Step 2: Establish the agent flow
Architecture pattern: Agent/Team/Workflow primitives compiled onto AgentOS runtime; control plane UI manages deployed agents; framework-agnostic hosting posture (2026 repositioning from pure framework to platform SDK)
Step 3: Implement tool integrations and policies
Integrate necessary tools, environment keys, and safety gates according to your architectural needs. Position in the ecosystem: Performance-and-platform lane of Python agent frameworks; alternatives: crewai (roles), langgraph (graphs); differentiates on instantiation speed and self-hosted control plane
Examples
Example 1: Minimal Agent Run
from agno.agent import Agent
from agno.models.openai import OpenAIChat
agent = Agent(model=OpenAIChat(id="gpt-5"), tools=[], markdown=True)
agent.print_response("Share a 2 sentence horror story")
# platform: agno.os AgentOS app -> serve with FastAPI
Best practices
- Follow the primary installation commands for Agno to ensure dependencies are resolved correctly.
- Configure model providers and API keys securely before starting the runtime.
- Use appropriate sandboxing or permission isolation if executing AI-generated code.