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Glean Core Workflow A
ASecurity'Execute Glean primary workflow: search, chat, and AI-powered answers
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- Added May 29, 2026
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[](https://www.skillsdirectory.com/skills/jeremylongshore-glean-core-workflow-a)---
name: glean-core-workflow-a
description: 'Execute Glean primary workflow: search, chat, and AI-powered answers
across enterprise data.
Use when building search integrations, implementing Glean chat, or creating AI assistants.
Trigger: "glean search API", "glean chat", "glean AI answers", "enterprise search".
'
allowed-tools: Read, Write, Edit, Bash(npm:*), Bash(curl:*), Grep
version: 1.0.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
tags:
- saas
- enterprise-search
- glean
compatibility: Designed for Claude Code
---
# Glean Core Workflow A: Search & Chat
## Overview
Build search and chat experiences using the Glean Client API. Covers full-text search with filters, AI-powered chat answers, and autocomplete suggestions.
## Instructions
### Step 1: Search with Filters and Facets
```typescript
const results = await fetch(`${GLEAN}/client/v1/search`, {
method: 'POST', headers: searchHeaders,
body: JSON.stringify({
query: 'kubernetes deployment best practices',
pageSize: 20,
requestOptions: {
datasourceFilter: 'confluence,github',
facetFilters: [{ fieldName: 'author', values: ['engineering-team'] }],
},
}),
}).then(r => r.json());
results.results?.forEach((r: any) => {
console.log(`[${r.datasource}] ${r.title}`);
console.log(` ${r.snippets?.[0]?.snippet ?? ''}`);
});
```
### Step 2: AI Chat (Glean Assistant)
```typescript
const chatResponse = await fetch(`${GLEAN}/client/v1/chat`, {
method: 'POST', headers: searchHeaders,
body: JSON.stringify({
messages: [{ role: 'USER', content: 'What is our deployment process for production?' }],
applicationId: 'my-app',
}),
}).then(r => r.json());
console.log('Answer:', chatResponse.messages?.[0]?.content);
console.log('Sources:', chatResponse.citations?.map((c: any) => c.title).join(', '));
```
### Step 3: Autocomplete / Suggestions
```typescript
const suggestions = await fetch(`${GLEAN}/client/v1/autocomplete`, {
method: 'POST', headers: searchHeaders,
body: JSON.stringify({ query: 'deploy', datasourceFilter: 'confluence' }),
}).then(r => r.json());
suggestions.results?.forEach((s: any) => console.log(` ${s.text}`));
```
## Error Handling
| Error | Cause | Solution |
|-------|-------|----------|
| Empty results | Query too specific or datasource not indexed | Broaden query, check datasource status |
| Chat returns no citations | Content not indexed for chat | Verify documents have body text |
| 403 on search | User permissions | Ensure token has search scope |
## Resources
- [Search API](https://developers.glean.com/api/client-api/search/search)
- [Chat API](https://developers.glean.com/api/client-api/search/overview)
## Next Steps
For bulk indexing workflow, see `glean-core-workflow-b`.
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