Lindy Core Workflow A: Agent Creation

Overview

Complete workflow for creating, configuring, and deploying Lindy AI agents.

Prerequisites

• Completed lindy-install-auth setup
• Understanding of agent use case
• Clear instructions/persona defined

Instructions

Step 1: Define Agent Specification

interface AgentSpec {
  name: string;
  description: string;
  instructions: string;
  tools: string[];
  model?: string;
  temperature?: number;
}

const agentSpec: AgentSpec = {
  name: 'Customer Support Agent',
  description: 'Handles customer inquiries and support tickets',
  instructions: `
    You are a helpful customer support agent.
    - Be polite and professional
    - Ask clarifying questions when needed
    - Escalate complex issues to human support
    - Always confirm resolution with the customer
  `,
  tools: ['email', 'calendar', 'knowledge-base'],
  model: 'gpt-4',
  temperature: 0.7,
};

Step 2: Create the Agent

import { Lindy } from '@lindy-ai/sdk';

const lindy = new Lindy({ apiKey: process.env.LINDY_API_KEY });

async function createAgent(spec: AgentSpec) {
  const agent = await lindy.agents.create({
    name: spec.name,
    description: spec.description,
    instructions: spec.instructions,
    tools: spec.tools,
    config: {
      model: spec.model || 'gpt-4',
      temperature: spec.temperature || 0.7,
    },
  });

  console.log(`Created agent: ${agent.id}`);
  return agent;
}

Step 3: Configure Agent Tools

async function configureTools(agentId: string, tools: string[]) {
  for (const tool of tools) {
    await lindy.agents.addTool(agentId, {
      name: tool,
      enabled: true,
    });
  }
  console.log(`Configured ${tools.length} tools`);
}

Step 4: Test the Agent

async function testAgent(agentId: string) {
  const testCases = [
    'Hello, I need help with my order',
    'Can you check my subscription status?',
    'I want to cancel my account',
  ];

  for (const input of testCases) {
    const result = await lindy.agents.run(agentId, { input });
    console.log(`Input: ${input}`);
    console.log(`Output: ${result.output}\n`);
  }
}

Output

• Fully configured AI agent
• Connected tools and integrations
• Tested agent responses
• Ready for deployment

Error Handling

Error	Cause	Solution
Tool not found	Invalid tool name	Check available tools list
Instructions too long	Exceeds limit	Summarize or split instructions
Model unavailable	Unsupported model	Use default gpt-4

Examples

Complete Agent Creation Flow

async function main() {
  // Create agent
  const agent = await createAgent(agentSpec);

  // Configure tools
  await configureTools(agent.id, agentSpec.tools);

  // Test agent
  await testAgent(agent.id);

  console.log(`Agent ${agent.id} is ready!`);
}

main().catch(console.error);

Resources

• Lindy Agent Creation
• Available Tools
• Model Options

Next Steps

Proceed to lindy-core-workflow-b for task automation workflows.