Skill UI

This tool optimizes the codebase indexing within Cursor. It processes your entire codebase, converting code chunks into vector embeddings stored in a vector database. This enables advanced @Codebase semantic search, allowing users to ask natural language questions (e.g., "Where is authentication handled?") and retrieve the most relevant code snippets, significantly improving AI context awareness across chat and coding tasks.

A comprehensive reference guide for structuring development projects within the Cursor IDE. It details best practices for directory layout, defining layered rules (covering global conventions, security constraints, and technology-specific patterns like API routes and database access), and optimizing indexing strategies. This ensures maximum AI effectiveness, improves code maintainability, and streamlines the entire development workflow.

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 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 for rapid incident response when Algolia search functionality fails. This runbook provides structured procedures for triage, differentiating between infrastructure outages and internal configuration errors (e.g., API keys, indexing failures). It includes severity classification, diagnosis steps, and code examples for immediate remediation, such as key rotation or implementing circuit breakers.

This guide provides comprehensive strategies for managing Algolia's rate limits and throttling mechanisms. It covers per-API-key limits (e.g., max queries per hour) and server-side indexing queue limits. Learn how to implement robust backoff strategies, exponential backoff, and controlled batch indexing using TypeScript examples to ensure application stability under high load.

This guide provides production-ready, high-quality patterns for integrating with Algolia Search v5. It covers critical architectural aspects such as implementing singleton client management, performing strongly typed searches, robust error handling (including specific API error codes), efficient batch indexing, and handling multi-tenant environments. Use these patterns to refactor existing code and establish reliable coding standards.

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 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.