glean-ci-integration
CI/CD for Glean connectors with automated indexing tests and search quality validation. Trigger: "glean CI", "glean GitHub Actions", "glean connector CI/CD".
Best use case
glean-ci-integration is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
CI/CD for Glean connectors with automated indexing tests and search quality validation. Trigger: "glean CI", "glean GitHub Actions", "glean connector CI/CD".
Teams using glean-ci-integration should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/glean-ci-integration/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How glean-ci-integration Compares
| Feature / Agent | glean-ci-integration | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
CI/CD for Glean connectors with automated indexing tests and search quality validation. Trigger: "glean CI", "glean GitHub Actions", "glean connector CI/CD".
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Glean CI Integration
## Overview
Set up CI/CD for Glean enterprise search integrations: run unit tests with mocked search and indexing responses on every PR, validate connector document transforms and search quality against a staging Glean instance on merge to main. Glean indexes content across SaaS tools, so CI pipelines focus on connector data transforms, indexing API calls, and search relevance regression testing.
## GitHub Actions Workflow
```yaml
# .github/workflows/glean-ci.yml
name: Glean CI
on:
pull_request:
paths: ['src/connectors/**', '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:
GLEAN_API_KEY: ${{ secrets.GLEAN_API_KEY }}
GLEAN_DOMAIN: ${{ secrets.GLEAN_DOMAIN }}
```
## Mock-Based Unit Tests
```typescript
// tests/glean-service.test.ts
import { describe, it, expect, vi } from 'vitest';
import { indexDocuments, searchDocuments } from '../src/glean-service';
vi.mock('../src/glean-client', () => ({
GleanClient: vi.fn().mockImplementation(() => ({
indexDocuments: vi.fn().mockResolvedValue({ indexed: 3, failed: 0 }),
search: vi.fn().mockResolvedValue({
results: [
{ title: 'Onboarding Guide', datasource: 'confluence', url: 'https://wiki.co/onboard' },
{ title: 'Deploy Process', datasource: 'notion', url: 'https://notion.so/deploy' },
],
totalResults: 2,
}),
getDatasources: vi.fn().mockResolvedValue(['confluence', 'notion', 'gdrive']),
})),
}));
describe('Glean Service', () => {
it('indexes documents and returns count', async () => {
const result = await indexDocuments([
{ title: 'Doc 1', body: 'Content', datasource: 'custom' },
]);
expect(result.indexed).toBe(3);
expect(result.failed).toBe(0);
});
it('searches across datasources', async () => {
const results = await searchDocuments('onboarding');
expect(results.totalResults).toBe(2);
expect(results.results[0].datasource).toBe('confluence');
});
});
```
## Integration Tests
```typescript
// tests/integration/glean.integration.test.ts
import { describe, it, expect } from 'vitest';
const hasKey = !!process.env.GLEAN_API_KEY;
describe.skipIf(!hasKey)('Glean Live API', () => {
it('searches enterprise content', async () => {
const res = await fetch(`https://${process.env.GLEAN_DOMAIN}-be.glean.com/api/v1/search`, {
method: 'POST',
headers: {
'Authorization': `Bearer ${process.env.GLEAN_API_KEY}`,
'Content-Type': 'application/json',
},
body: JSON.stringify({ query: 'test', pageSize: 1 }),
});
expect(res.status).toBe(200);
const body = await res.json();
expect(body).toHaveProperty('results');
});
});
```
## Error Handling
| CI Issue | Cause | Fix |
|----------|-------|-----|
| `401 Unauthorized` | Invalid API token or wrong domain | Verify token at admin.glean.com |
| Indexing returns 0 documents | Document format doesn't match schema | Validate document structure against Glean connector spec |
| Search quality regression | Index not yet updated | Add wait between indexing and search quality checks |
| Datasource not found | Connector not configured in staging | Set up test datasource in Glean admin before CI runs |
| Rate limit (429) | Too many indexing calls | Batch documents (max 100 per call) and add throttling |
## Resources
- [Glean Developer Portal](https://developers.glean.com/)
- [Glean Indexing API](https://developers.glean.com/docs/indexing_api/overview)
- [GitHub Actions Secrets](https://docs.github.com/en/actions/security-guides/encrypted-secrets)
## Next Steps
For deployment patterns, see `glean-deploy-integration`.Related Skills
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