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Automates the CI/CD process for Glean enterprise search connectors. This tool runs comprehensive unit tests with mocked responses on every Pull Request, and executes integration tests against a staging Glean instance upon merging to the main branch. It validates connector data transforms, indexing API calls, and performs search relevance regression testing to ensure high search quality.

A comprehensive guide designed to diagnose and resolve common technical errors encountered when integrating with the Glean enterprise search API. It covers critical areas such as token type mismatches, indexing pipeline failures, permission restrictions, and rate limiting, providing actionable fixes for maintaining seamless search functionality.

This workflow demonstrates the core capabilities of the Glean Client API, allowing users to build comprehensive knowledge assistants. It covers advanced full-text search with filters and facets, implements AI-powered chat for contextual Q&A, and provides autocomplete suggestions. Ideal for integrating deep search and conversational AI into enterprise applications.

This skill implements Role-Based Access Control (RBAC) for Glean Enterprise Search. It establishes a secure framework by mapping permissions from various source systems (like AD/Okta) to the centralized search index. The functionality allows management of distinct roles (Super Admin, Admin, Content Manager), performing detailed document access checks via API, and maintaining comprehensive audit logs. This is crucial for maintaining compliance with standards like GDPR and SOC 2.

This skill demonstrates the complete workflow for integrating with the Glean platform. It guides users through three core steps: setting up a custom data source using the Indexing API, programmatically indexing documents, and executing advanced search queries using the Client API. This is essential for developers starting new Glean connectors or needing to test their search pipelines.

This comprehensive runbook provides detailed procedures for diagnosing and resolving critical incidents within the Glean enterprise search platform. It covers all severity levels (P1-P4) and failure modes, including API outages, connector synchronization failures, indexing backlogs, and permission drift. It includes diagnostic steps, advanced troubleshooting playbooks, and communication templates for technical support and engineering teams.

This comprehensive guide details how to authenticate and configure connections to the Glean enterprise search platform. It covers the distinct setup for the Indexing API (used for pushing data into the search index) and the Client API (used for searching and retrieving results). Essential for developers integrating custom data sources or building advanced search features.

A comprehensive development workflow solution for integrating with the Glean enterprise search API. It enables developers to simulate local search responses, mock data sources, and test custom connectors and UIs without needing a live Glean deployment. Users can toggle between mock mode for rapid iteration and sandbox mode for validation against a real Glean instance, ensuring a fast feedback loop for building robust enterprise search applications.

A comprehensive technical guide detailing the process of migrating large-scale enterprise search platforms from sources like Elasticsearch or Algolia to Glean. It covers data export, schema transformation, using bulk indexing APIs, creating data sources, and validating search quality for smooth, large-scale deployment.

This comprehensive guide details the setup and deployment workflow for Glean enterprise search across development, staging, and production environments. It emphasizes strict environment isolation by managing separate datasources, API tokens, and configurations for each stage. The skill covers best practices for promotion workflows, validation steps, and error handling, ensuring search relevance and data integrity during scaling and updates.

This tool provides comprehensive observability for enterprise search systems (Glean). It tracks critical metrics such as search latency (p95), zero-result query rates, indexing throughput, and stale content ratios. By monitoring connector sync status and detecting indexing degradation, it allows teams to proactively maintain search relevance and ensure sub-second response times, preventing silent data quality decay.

This skill provides comprehensive guidelines and implementation examples for managing rate limits when interacting with the Glean Indexing and Search APIs. It includes a custom RateLimiter class, robust retry logic (handling 429 errors and server errors), and best practices for batch processing large datasets, ensuring stable, high-volume data ingestion pipelines.