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.zipInstalls to .claude/skills/juicebox-ci-integration
Activation
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Configure Juicebox CI/CD.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
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 Issue | Cause | Fix |
|---|---|---|
401 Unauthorized | Invalid API key | Regenerate at juicebox.ai account settings |
Analysis stuck on processing | Large dataset or complex query | Increase polling timeout to 120s |
| Dataset not found (404) | Dataset ID changed or deleted | Use listDatasets to get a valid ID dynamically |
| Rate limit (429) | Too many concurrent analyses | Queue analyses and limit to 2 parallel runs |
| Empty insights array | Insufficient data for AI analysis | Ensure test dataset has 100+ rows with varied data |
Resources
- Juicebox Documentation
- GitHub Actions Secrets
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
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.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| juicebox-ci-integration (this skill) | 1 | 26d | Review | Intermediate |
| e2e-testing-patterns | 8 | 2mo | No flags | Intermediate |
| testing-workflow | 16 | 9mo | Review | Intermediate |
| perf-lighthouse | 13 | 5mo | Review | Intermediate |
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