JU

juicebox-ci-integration

Automates testing and validation for Juicebox API integrations within GitHub Actions.

Install

mkdir -p .claude/skills/juicebox-ci-integration && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/5453" && unzip -o skill.zip -d .claude/skills/juicebox-ci-integration && rm skill.zip

Installs to .claude/skills/juicebox-ci-integration

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Configure Juicebox CI/CD.
25 charsno explicit “when” trigger
Intermediate

Key capabilities

  • Run unit tests with mocked dataset responses
  • Validate live API connectivity
  • Automate testing on pull requests
  • Verify dataset upload logic
  • Test result parsing workflows

How it works

It configures GitHub Actions to run unit tests using mocked client responses and integration tests that verify live API connectivity. It ensures data analysis and dataset upload workflows function correctly before merging.

Inputs & outputs

You give it
Source code and test suite
You get back
CI pipeline validation status

When to use juicebox-ci-integration

  • Automate testing for Juicebox integrations
  • Configure GitHub Actions for CI
  • Validate API connectivity in build process

About this skill

Juicebox CI Integration

Overview

Set up CI/CD for Juicebox AI data analysis integrations: run unit tests with mocked dataset and analysis responses on every PR, validate live API connectivity for data queries on merge to main. Juicebox provides AI-powered data exploration and visualization, so CI pipelines verify dataset upload logic, analysis execution, and result parsing workflows.

GitHub Actions Workflow

# .github/workflows/juicebox-ci.yml
name: Juicebox CI
on:
  pull_request:
    paths: ['src/juicebox/**', 'tests/**']
  push:
    branches: [main]

jobs:
  unit-tests:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-node@v4
        with: { node-version: '20' }
      - run: npm ci
      - run: npm test -- --reporter=verbose

  integration-tests:
    if: github.ref == 'refs/heads/main'
    needs: unit-tests
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-node@v4
        with: { node-version: '20' }
      - run: npm ci
      - run: npm run test:integration
        env:
          JUICEBOX_API_KEY: ${{ secrets.JUICEBOX_API_KEY }}

Mock-Based Unit Tests

// tests/juicebox-service.test.ts
import { describe, it, expect, vi } from 'vitest';
import { analyzeDataset, getAnalysisResults } from '../src/juicebox-service';

vi.mock('../src/juicebox-client', () => ({
  JuiceboxClient: vi.fn().mockImplementation(() => ({
    createAnalysis: vi.fn().mockResolvedValue({
      analysisId: 'ana_abc123',
      status: 'processing',
      datasetId: 'ds_xyz',
    }),
    getAnalysis: vi.fn().mockResolvedValue({
      analysisId: 'ana_abc123',
      status: 'completed',
      results: {
        summary: 'Revenue increased 15% QoQ',
        charts: [{ type: 'bar', title: 'Revenue by Quarter' }],
        insights: ['Q4 drove majority of growth', 'APAC region outperformed'],
      },
    }),
    listDatasets: vi.fn().mockResolvedValue({
      datasets: [{ id: 'ds_xyz', name: 'Sales Data', rowCount: 50000 }],
    }),
  })),
}));

describe('Juicebox Service', () => {
  it('creates an analysis from dataset', async () => {
    const result = await analyzeDataset('ds_xyz', 'What drove revenue growth?');
    expect(result.analysisId).toBe('ana_abc123');
    expect(result.status).toBe('processing');
  });

  it('retrieves completed analysis with insights', async () => {
    const results = await getAnalysisResults('ana_abc123');
    expect(results.status).toBe('completed');
    expect(results.results.insights).toHaveLength(2);
  });
});

Integration Tests

// tests/integration/juicebox.integration.test.ts
import { describe, it, expect } from 'vitest';

const hasKey = !!process.env.JUICEBOX_API_KEY;

describe.skipIf(!hasKey)('Juicebox Live API', () => {
  it('lists available datasets', async () => {
    const res = await fetch('https://api.juicebox.ai/v1/datasets', {
      headers: { Authorization: `Bearer ${process.env.JUICEBOX_API_KEY}` },
    });
    expect(res.status).toBe(200);
    const body = await res.json();
    expect(body).toHaveProperty('datasets');
  });
});

Error Handling

CI IssueCauseFix
401 UnauthorizedInvalid API keyRegenerate at juicebox.ai account settings
Analysis stuck on processingLarge dataset or complex queryIncrease polling timeout to 120s
Dataset not found (404)Dataset ID changed or deletedUse listDatasets to get a valid ID dynamically
Rate limit (429)Too many concurrent analysesQueue analyses and limit to 2 parallel runs
Empty insights arrayInsufficient data for AI analysisEnsure test dataset has 100+ rows with varied data

Resources

Next Steps

See juicebox-deploy-integration.

When not to use it

  • When API keys are missing in production environments
  • When test datasets have fewer than 100 rows

Prerequisites

GitHub Actions environmentNode.js runtime

Limitations

  • 401 Unauthorized errors with invalid API keys
  • Analysis stuck on processing for large datasets
  • Rate limits on concurrent analyses

How it compares

This approach uses specific mock-based unit tests for Juicebox analysis workflows rather than generic integration testing.

Compared to similar skills

juicebox-ci-integration side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
juicebox-ci-integration (this skill)126dReviewIntermediate
e2e-testing-patterns82moNo flagsIntermediate
testing-workflow169moReviewIntermediate
perf-lighthouse135moReviewIntermediate

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