Lindy Agent Creation Workflow

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

Sby Skills Guide Bot
Data & AIIntermediate
7/26/2026
Claude Code
#lindy#ai-agents#agent-configuration#typescript#workflow

Recommended for

Automated summary

Describes the core workflow for creating, configuring, and testing an AI agent on the Lindy platform through its TypeScript SDK.

Strengths

  • Walks through the full sequence: specification, creation, tool attachment, then testing with concrete cases
  • Supplies directly reusable TypeScript snippets (AgentSpec interface, SDK calls)
  • Includes a troubleshooting table for common errors (invalid tool, oversized instructions, unavailable model)
  • States prerequisites clearly and points to the follow-up workflow for task automation

Limitations

  • Fully tied to Lindy's SDK and APIs, whose exact signatures are not verified here
  • Testing is limited to console input/output examples with no assertions or test harness
  • Does not address secret handling beyond an environment variable, nor production deployment
When to use it

Use it when starting a new Lindy agent and you want an ordered path from spec definition to first test runs.

When not to use it

Skip it if you are not on the Lindy platform or you need vendor-neutral agent design guidance.

Security analysis

Safe
Quality score82/100

The skill is a pure documentation/instruction file for creating Lindy AI agents via the TypeScript SDK. Declared allowed-tools are limited to Read, Write, Edit with no bash, network, or system-modifying operations. The API key is referenced via process.env.LINDY_API_KEY rather than hardcoded or exfiltrated, and there are no curl|sh, destructive commands, obfuscated payloads, or safety-disabling instructions.

No concerns found

How this analysis is made

Examples

Create a support agent
Use the Lindy core workflow to create a customer support agent with email and knowledge-base tools, then run a few test inputs and show me the outputs.
Define and test an agent spec
Build a Lindy agent for handling subscription questions: write the AgentSpec in TypeScript, create it via the SDK, attach the calendar and email tools, and test it with three sample queries.
Configure tools on an existing agent
I already have a Lindy agent ID — help me configure its tools and run the test cases from the lindy-core-workflow-a skill.

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

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

Next Steps

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

From the file to a first result

The download contains exactly the content displayed on this page. This copy may differ from the latest version in the source repository.

View the source and supporting files

This download contains SKILL.md only. Any scripts, references, templates and dependencies are not included. Get the required files from the source, preserving their directory structure, before continuing.

1. Download the file

Download SKILL.md

From the root of a test project, save the file as .skill-downloads/lindy-agent-creation-workflow-ms1aw589/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.

Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.

mkdir -p '.skill-downloads/lindy-agent-creation-workflow-ms1aw589' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/lindy-agent-creation-workflow-ms1aw589/download' --output '.skill-downloads/lindy-agent-creation-workflow-ms1aw589/SKILL.md.part' && mv '.skill-downloads/lindy-agent-creation-workflow-ms1aw589/SKILL.md.part' '.skill-downloads/lindy-agent-creation-workflow-ms1aw589/SKILL.md'

2. Check prerequisites

Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.

Tools declared by the author (check availability in your agent): Read, Write, Edit

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

The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.

3. Load the skill

After inspection, copy the complete folder into your project using one of the commands below, then open a new tool session. The command stops if a folder with the same name already exists: compare the files before replacing it.

Claude Code
test -f '.skill-downloads/lindy-agent-creation-workflow-ms1aw589/SKILL.md' && test -s '.skill-downloads/lindy-agent-creation-workflow-ms1aw589/SKILL.md' && mkdir -p '.claude/skills' && test ! -e '.claude/skills/lindy-core-workflow-a' && cp -R '.skill-downloads/lindy-agent-creation-workflow-ms1aw589' '.claude/skills/lindy-core-workflow-a'

OpenSkills

OpenSkills must already be installed. The local install/read procedure is checked with OpenSkills 1.5.0, which requires Node.js ≥ 20.6.0. Catalog slugs are not resolved automatically.

Official OpenSkills installation
openskills install './.skill-downloads/lindy-agent-creation-workflow-ms1aw589'

openskills read 'lindy-agent-creation-workflow-ms1aw589'

Reading should display the installed file content and its base directory. It does not run the skill or install its dependencies.

For an agent that reads AGENTS.md, then sync the index. This command changes AGENTS.md: review the diff before using it.

openskills sync

Manual method or another tool: attach SKILL.md to a conversation, or open it in an agent that can read files. Include any required supporting resources. No universal folder is recognized by every tool.

4. Try a first task

Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:

Read .skill-downloads/lindy-agent-creation-workflow-ms1aw589/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.

Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.

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