Building Scalable AI Agents with Agno Skills: A Planner Agent Case Study

In the rapidly evolving landscape of AI agents, structure and reusability are paramount. We often build agents that are great at one thing, but fail when asked to coordinate complex workflows. Enter Agno Skills - a powerful feature in the Agno framework that allows you to package specialized knowledge and capabilities into reusable modules.

In this post, we’ll explore how to build a Planner Agent that uses a custom Task Planning Skill to decompose ambiguous goals into actionable execution plans.

What are Agno Skills?

Think of an Agent as a worker and a Skill as a handbook or toolbelt. You shouldn't have to hardcode every procedure into the agent's system prompt. Instead, you can define a Skill—a directory containing instructions (SKILL.md), references, and resources—that the agent can "read" and apply when needed.

The Use Case: A Planner Agent
I built a Planner Agent designed to take a high-level goal (e.g., "Launch a marketing website") and break it down into atomic tasks for other specialized agents (Design, Copy, SEO, Engineering).

How I Built It

1. The Skill (skills/task-planning/): I defined the planning methodology in SKILL.md, instructing the agent to:
   • Decompose goals into atomic tasks.
   • Map dependencies (Concept → Copy → SEO).
   • Assign specific roles.
2. The Agent: I initialized a simple Agno Agent using OpenAI (or Ollama!) and gave it the instruction to use the task-planning skill.

The Result
When given the goal "Launch a marketing website", the agent doesn't just chat; it outputs a structured JSON-like plan with task IDs, dependencies, and assigned agents. This plan can then be fed programmatically into an execution pipeline.

Why This Matters

• Separation of Concerns: Your agent logic stays clean; your domain logic lives in skills.
• Reusability: You can plug this task-planning skill into a Project Manager Agent or a QA Agent.
• Model Agnostic: We seamlessly switched this agent from GPT-4o to a local Ollama model (gemma3:4b) just by changing a flag. The skill remained exactly the same.

Agno Skills bring software engineering principles to prompt engineering. By treating capabilities as modular assets, we can build multi-agent systems that are robust, testable, and infinitely scalable.

Checkout the Github repo here.