glean-core-workflow-a

v2026.09.24

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".

GitHub
安装命令
npx skhub add jeremylongshore/glean-core-workflow-a
Markdown
SKILL.md

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.

Prerequisites

  • A scoped search identity, approved datasource filter, and synthetic terms that cannot retrieve company-sensitive material.
  • User-consent and retention policy for any analytics, chat history, or feedback capture.
  • A rollback path that disables the client or filter without changing source documents or connector ACLs.

Instructions

Step 1: Search with Filters and Facets

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)

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

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

ErrorCauseSolution
Empty resultsQuery too specific or datasource not indexedBroaden query, check datasource status
Chat returns no citationsContent not indexed for chatVerify documents have body text
403 on searchUser permissionsEnsure token has search scope

Output

Return a redacted workflow receipt containing datasource scope, correlation ID, result-count band, allow/deny outcomes, and fallback used. Never record query text, titles, snippets, transcripts, or credentials.

Examples

Run a fictional query against sandbox-handbook, verify one authorized identity sees the sample while a denied identity sees none, and record scope=sandbox-handbook; allow=1; deny=0; fallback=none.

Resources

Next Steps

For bulk indexing workflow, see glean-core-workflow-b.

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最新版本元数据

版本

v2026.09.24

发布时间

Sep 24, 2026

分类

未分类

许可证

MIT

源路径

skills/.curated/glean-core-workflow-a

默认分支

main

最新提交

e5a6c3b

Tree SHA

c2dc8e8