Skill UI

This skill provides a comprehensive workflow for integrating external data sources into the Glean enterprise search platform. It covers setting up custom datasources, performing high-volume bulk document indexing using the Indexing API, and granularly managing document permissions (read/write access) to ensure accurate and secure search results for large organizations. Ideal for data engineers and developers building internal knowledge bases.

This guide provides a comprehensive framework for optimizing operational costs within the Glean enterprise search platform. It details best practices for content governance, including filtering stale drafts and limiting document sizes, optimizing data source connectors, and implementing incremental indexing strategies. Implementing these measures helps minimize indexing volume and usage fees, maximizing search value while maintaining cost efficiency.

A comprehensive debug bundle designed to collect diagnostic evidence from Glean enterprise search integrations. It systematically checks datasource configuration, indexing status, search quality metrics, and connectivity logs. This tool is crucial for troubleshooting complex issues like connector failures, stale indexed data, and permission-based search gaps without needing direct admin console access.

This skill provides a complete solution for deploying Glean custom connectors as scheduled jobs on container platforms (e.g., Cloud Run). It covers building a production-ready Docker image to manage document ingestion, custom data source connectivity, and search query execution. Includes robust health checks and rolling update strategies to ensure continuous, high-availability indexing for enterprise search environments.

Provides advanced best practices for optimizing Glean's enterprise search performance and scalability. Covers critical techniques such as implementing effective batch sizing, caching strategies, connection pooling, and robust rate limit management to significantly reduce search latency and maintain high-throughput indexing for massive, diverse datasets.

A comprehensive checklist designed to validate the deployment, robustness, and security of an enterprise search system powered by Glean. It covers critical areas such as API integration, secrets management, error handling, monitoring, and permissions, ensuring a stable and reliable user experience in a production setting.

This module provides production-ready patterns for interacting with the Glean enterprise search API. It features a typed client, implementing singleton patterns and robust mechanisms for search and indexing. Key patterns include batch pagination, comprehensive error handling (e.g., retries for rate limits), and a fluent request builder for executing complex, reliable API calls.

A comprehensive guide detailing security best practices for integrating and managing enterprise search with Glean. It covers critical topics such as indexing token management, validating webhook signatures, implementing input validation using Zod, and techniques for data redaction, ensuring that sensitive information is protected across the entire search lifecycle.

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 governs the secure ingestion and indexing of enterprise documents from diverse connectors (e.g., Google Drive, Confluence, Jira). Key functions include mandatory PII filtering (stripping emails, phones, SSNs) before indexing, preserving strict permission boundaries, and enforcing data retention policies to ensure compliance with global regulations like GDPR and CCPA.