# Creating an AI Agent Learn how to create an Mastra agent that can be used within your workflows for more intelligent content processing. ## Creating a Content Analysis Agent Create a new file for your agent in the `src/mastra/agents` directory. Use `content-agent.ts` as the name of the file with the following contents: ```typescript // src/mastra/agents/content-agent.ts import { openai } from "@ai-sdk/openai"; import { Agent } from "@mastra/core/agent"; export const contentAgent = new Agent({ name: "Content Agent", description: "AI agent for analyzing and improving content", instructions: ` You are a professional content analyst. Your role is to: 1. Analyze content for clarity and engagement 2. Identify the main themes and topics 3. Provide a quality score from 1-10 4. Suggest specific improvements Always provide constructive, actionable feedback. `, model: openai("gpt-4o-mini"), }); ``` ## Understanding the Agent - **Name**: Unique identifier for the agent - **Description**: What the agent does - **Instructions**: Detailed prompts that guide the AI's behavior - **Model**: Which AI model to use (GPT-4o-mini is fast and cost-effective) ## Registering and Testing Your Agent Open your `src/mastra/index.ts` file and add your agent (you may need to append it to the agents object in the Mastra class): ```typescript // Import your workflow import { contentAgent } from "./agents/content-agent"; export const mastra = new Mastra({ // Register your agent here agents: { contentAgent, }, // ...Existing code }); ``` You can test this agent in the Playground by navigating to the Agents tab and selecting `content-agent`. Use the chat interface to validate the agent is working. The agent should provide analysis of the content, including themes, quality assessment, and improvement suggestions. ## Why Use Agents in Workflows? Agents add intelligence to workflows by: - **Understanding context**: AI can interpret meaning, not just process data - **Generating insights**: Provide analysis that simple logic cannot - **Adapting responses**: Give different feedback based on content type - **Natural language output**: Communicate results in human-readable form Your AI agent is ready! Next, you'll learn how to integrate it into a workflow step.