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Lindy Core Workflow A

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Core Lindy workflow for creating and configuring AI agents. Use when building new agents, defining agent behaviors, or setting up agent capabilities. Trigger with phrases like "create lindy agent", "build lindy agent", "lindy agent workflow", "configure lindy agent".

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  • Added February 7, 2026
ai-agentstypescriptapi

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  • api

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Scanned February 12, 2026

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SKILL.md
---
name: lindy-core-workflow-a
description: |
  Core Lindy workflow for creating and configuring AI agents.
  Use when building new agents, defining agent behaviors,
  or setting up agent capabilities.
  Trigger with phrases like "create lindy agent", "build lindy agent",
  "lindy agent workflow", "configure lindy agent".
allowed-tools: Read, Write, Edit
version: 1.0.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
---

# 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
```typescript
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
```typescript
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
```typescript
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
```typescript
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
```typescript
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](https://docs.lindy.ai/agents/create)
- [Available Tools](https://docs.lindy.ai/tools)
- [Model Options](https://docs.lindy.ai/models)

## Next Steps
Proceed to `lindy-core-workflow-b` for task automation workflows.

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