jeremylongshore

lindy-ci-integration

@jeremylongshore/lindy-ci-integration
jeremylongshore
1,004
123 forks
Updated 1/18/2026
View on GitHub

Configure Lindy AI CI/CD integration with GitHub Actions and testing. Use when setting up automated testing, configuring CI pipelines, or integrating Lindy tests into your build process. Trigger with phrases like "lindy CI", "lindy GitHub Actions", "lindy automated tests", "CI lindy pipeline".

Installation

$skills install @jeremylongshore/lindy-ci-integration
Claude Code
Cursor
Copilot
Codex
Antigravity

Details

Pathplugins/saas-packs/lindy-pack/skills/lindy-ci-integration/SKILL.md
Branchmain
Scoped Name@jeremylongshore/lindy-ci-integration

Usage

After installing, this skill will be available to your AI coding assistant.

Verify installation:

skills list

Skill Instructions


name: lindy-ci-integration description: | Configure Lindy AI CI/CD integration with GitHub Actions and testing. Use when setting up automated testing, configuring CI pipelines, or integrating Lindy tests into your build process. Trigger with phrases like "lindy CI", "lindy GitHub Actions", "lindy automated tests", "CI lindy pipeline". allowed-tools: Read, Write, Edit, Bash(gh:*) version: 1.0.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io

Lindy CI Integration

Overview

Configure CI/CD pipelines for Lindy AI agent testing and deployment.

Prerequisites

  • GitHub repository with Actions enabled
  • Lindy test API key
  • npm/pnpm project configured

Instructions

Step 1: Create GitHub Actions Workflow

# .github/workflows/lindy-ci.yml
name: Lindy CI

on:
  push:
    branches: [main]
  pull_request:
    branches: [main]

env:
  LINDY_API_KEY: ${{ secrets.LINDY_API_KEY }}
  LINDY_ENVIRONMENT: test

jobs:
  test:
    runs-on: ubuntu-latest

    steps:
      - uses: actions/checkout@v4

      - name: Setup Node.js
        uses: actions/setup-node@v4
        with:
          node-version: '20'
          cache: 'npm'

      - name: Install dependencies
        run: npm ci

      - name: Run linting
        run: npm run lint

      - name: Run type check
        run: npm run typecheck

      - name: Run unit tests
        run: npm test

      - name: Run Lindy integration tests
        run: npm run test:integration
        env:
          LINDY_API_KEY: ${{ secrets.LINDY_TEST_API_KEY }}

      - name: Upload coverage
        uses: codecov/codecov-action@v3
        with:
          files: ./coverage/lcov.info

Step 2: Configure Test API Key

# Add secret to GitHub repository
gh secret set LINDY_TEST_API_KEY --body "lnd_test_xxx"

# Verify secret is set
gh secret list

Step 3: Create Integration Tests

// tests/integration/lindy.test.ts
import { Lindy } from '@lindy-ai/sdk';

describe('Lindy Integration', () => {
  let lindy: Lindy;
  let testAgentId: string;

  beforeAll(async () => {
    lindy = new Lindy({ apiKey: process.env.LINDY_API_KEY });

    // Create test agent
    const agent = await lindy.agents.create({
      name: 'CI Test Agent',
      instructions: 'Respond with "OK" to any input.',
    });
    testAgentId = agent.id;
  });

  afterAll(async () => {
    // Cleanup test agent
    await lindy.agents.delete(testAgentId);
  });

  test('agent responds correctly', async () => {
    const result = await lindy.agents.run(testAgentId, {
      input: 'Test message',
    });
    expect(result.output).toContain('OK');
  });

  test('handles rate limits gracefully', async () => {
    const promises = Array(5).fill(null).map(() =>
      lindy.agents.run(testAgentId, { input: 'Test' })
    );
    const results = await Promise.allSettled(promises);
    const successful = results.filter(r => r.status === 'fulfilled');
    expect(successful.length).toBeGreaterThan(0);
  });
});

Step 4: Add PR Checks

# .github/workflows/lindy-pr-check.yml
name: Lindy PR Check

on:
  pull_request:
    types: [opened, synchronize]

jobs:
  validate-agents:
    runs-on: ubuntu-latest

    steps:
      - uses: actions/checkout@v4

      - name: Setup Node.js
        uses: actions/setup-node@v4
        with:
          node-version: '20'

      - name: Install dependencies
        run: npm ci

      - name: Validate agent configurations
        run: npm run validate:agents

      - name: Check for sensitive data
        run: |
          if grep -r "lnd_" --include="*.ts" --include="*.js" .; then
            echo "Found hardcoded API keys!"
            exit 1
          fi

Output

  • Automated test pipeline
  • PR checks configured
  • Coverage reports uploaded
  • Integration test suite

Error Handling

IssueCauseSolution
Secret not foundNot configuredAdd via gh secret set
Tests timeoutAgent slowIncrease jest timeout
Rate limitedToo many testsAdd delays or use test key

Examples

Matrix Testing

jobs:
  test:
    strategy:
      matrix:
        node: [18, 20, 22]
        os: [ubuntu-latest, macos-latest]
    runs-on: ${{ matrix.os }}
    steps:
      - uses: actions/setup-node@v4
        with:
          node-version: ${{ matrix.node }}

Resources

Next Steps

Proceed to lindy-deploy-integration for deployment automation.

More by jeremylongshore

View all
rabbitmq-queue-setup
1,004

Rabbitmq Queue Setup - Auto-activating skill for Backend Development. Triggers on: rabbitmq queue setup, rabbitmq queue setup Part of the Backend Development skill category.

model-evaluation-suite
1,004

evaluating-machine-learning-models: This skill allows Claude to evaluate machine learning models using a comprehensive suite of metrics. It should be used when the user requests model performance analysis, validation, or testing. Claude can use this skill to assess model accuracy, precision, recall, F1-score, and other relevant metrics. Trigger this skill when the user mentions "evaluate model", "model performance", "testing metrics", "validation results", or requests a comprehensive "model evaluation".

neural-network-builder
1,004

building-neural-networks: This skill allows Claude to construct and configure neural network architectures using the neural-network-builder plugin. It should be used when the user requests the creation of a new neural network, modification of an existing one, or assistance with defining the layers, parameters, and training process. The skill is triggered by requests involving terms like "build a neural network," "define network architecture," "configure layers," or specific mentions of neural network types (e.g., "CNN," "RNN," "transformer").

oauth-callback-handler
1,004

Oauth Callback Handler - Auto-activating skill for API Integration. Triggers on: oauth callback handler, oauth callback handler Part of the API Integration skill category.