Claude-skill-registry lindy-sdk-patterns

install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/lindy-sdk-patterns-helixdevelopment-helixagent" ~/.claude/skills/majiayu000-claude-skill-registry-lindy-sdk-patterns && rm -rf "$T"
manifest: skills/data/lindy-sdk-patterns-helixdevelopment-helixagent/SKILL.md
source content

Lindy SDK Patterns

Overview

Essential SDK patterns and best practices for Lindy AI agent development.

Prerequisites

  • Completed
    lindy-install-auth
    setup
  • Basic understanding of async/await
  • Familiarity with TypeScript

Instructions

Pattern 1: Client Singleton

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

let client: Lindy | null = null;

export function getLindyClient(): Lindy {
  if (!client) {
    client = new Lindy({
      apiKey: process.env.LINDY_API_KEY!,
      timeout: 30000,
    });
  }
  return client;
}

Pattern 2: Agent Factory

// agents/factory.ts
import { getLindyClient } from '../lib/lindy';

interface AgentConfig {
  name: string;
  instructions: string;
  tools?: string[];
}

export async function createAgent(config: AgentConfig) {
  const lindy = getLindyClient();

  const agent = await lindy.agents.create({
    name: config.name,
    instructions: config.instructions,
    tools: config.tools || [],
  });

  return agent;
}

Pattern 3: Retry with Backoff

async function runWithRetry<T>(
  fn: () => Promise<T>,
  maxRetries = 3
): Promise<T> {
  for (let i = 0; i < maxRetries; i++) {
    try {
      return await fn();
    } catch (error: any) {
      if (error.status === 429 && i < maxRetries - 1) {
        await new Promise(r => setTimeout(r, Math.pow(2, i) * 1000));
        continue;
      }
      throw error;
    }
  }
  throw new Error('Max retries exceeded');
}

Pattern 4: Streaming Responses

async function streamAgentResponse(agentId: string, input: string) {
  const lindy = getLindyClient();

  const stream = await lindy.agents.runStream(agentId, { input });

  for await (const chunk of stream) {
    process.stdout.write(chunk.delta);
  }
  console.log(); // newline
}

Output

  • Reusable client singleton pattern
  • Agent factory for consistent creation
  • Robust error handling with retries
  • Streaming support for real-time output

Error Handling

PatternUse CaseBenefit
SingletonConnection reuseReduced overhead
FactoryAgent creationConsistency
RetryRate limitsReliability
StreamingLong responsesBetter UX

Examples

Complete Agent Service

// services/agent-service.ts
import { getLindyClient } from '../lib/lindy';

export class AgentService {
  private lindy = getLindyClient();

  async createAndRun(name: string, instructions: string, input: string) {
    const agent = await this.lindy.agents.create({ name, instructions });
    const result = await this.lindy.agents.run(agent.id, { input });
    return { agent, result };
  }

  async listAgents() {
    return this.lindy.agents.list();
  }

  async deleteAgent(id: string) {
    return this.lindy.agents.delete(id);
  }
}

Resources

Next Steps

Proceed to

lindy-core-workflow-a
for agent creation workflows.