agno
0Agno is an AI agent skill that allows users to add specific capabilities to their AI systems. It is suitable for developers looking to enhance the functionality of their applications.
1410Updated Yesterday
AI Agent Skills
Quick InstallView Source
$ npx skills add https://github.com/delorenj/skills --skill agnoOverview
About This Skill
Agno is an AI agent framework that enables developers to build production-ready multi-agent systems with tools, memory, and structured outputs. It supports multi-agent teams with role-based delegation, complex workflows with conditional branching and loops, and integrates with Model Context Protocol (MCP) servers via stdio, SSE, or HTTP transports. The framework includes session memory storage via PostgreSQL or SQLite, knowledge base functionality for RAG and document processing, and AgentOS—a FastAPI-based runtime for deploying agents as production APIs. Developers use Agno to create autonomous agents, orchestrate agent collaboration, debug agent behavior with telemetry, and optimize performance with retries and rate limiting.
How to Use
Install using the command provided to add the skill to your project.
Use Cases
Enhance AI capabilities for user-specific tasks
Integrate into custom AI workflows
Develop and test new AI functionalities
Tags
Setup & Installation
Quick Install
Terminal
$ npx skills add https://github.com/delorenj/skills --skill agnoAlternative Install (Git Clone)
git clone https://github.com/delorenj/skillsRequirements
- Claude Code or compatible AI agent
Quick Start Guide
1
Install the Skill
Copy the install command above and run it in your terminal.
2
Open Your AI Agent
Launch Claude Code, Cursor, or your preferred AI coding agent.
3
Try It Out
Use the prompt template or examples below to test the skill.
4
Customize
Adapt the skill to your specific use case and workflow.
Usage Examples
Prompt Template
I want to enhance my AI system with [SPECIFIC_CAPABILITY] using agno. Can you provide a step-by-step guide on how to implement this skill in my [APPLICATION_TYPE] for [USE_CASE]? Include code snippets or configuration examples if available.
Example Output
# Agno Integration Guide for [SPECIFIC_CAPABILITY]
## Overview
Successfully integrated agno's [SPECIFIC_CAPABILITY] into your [APPLICATION_TYPE] application. Below are the key results and configuration details:
### Key Metrics
- **Response Time Improvement**: Reduced from 800ms to 250ms
- **Accuracy Rate**: 94.2% (up from 78% baseline)
- **User Adoption**: 89% of test users reported improved experience
### Configuration Snippet
```javascript
// agno configuration for [APPLICATION_TYPE]
const agnoConfig = {
capability: "[SPECIFIC_CAPABILITY]",
apiKey: "your-api-key-here",
options: {
timeout: 5000,
retries: 3,
fallback: "default_response"
}
};
```
### Implementation Steps
1. **Installation**: Added agno SDK via npm
2. **Configuration**: Set up environment variables
3. **Testing**: Verified with 500 test cases
4. **Deployment**: Gradual rollout to 20% of users
### Performance Logs
- **Peak Usage**: 1,200 requests/minute
- **Error Rate**: 0.3% (below industry average)
- **Memory Usage**: Increased by 12% (acceptable for this capability)
Would you like me to analyze any specific aspect of this implementation further?Find the right skills for your stack
Take a free 3-minute scan and get personalized AI skill recommendations.
Take free scan