Skill UI

This comprehensive guide teaches developers how to build advanced, interactive, and data-driven components within Framer using React. It covers creating components with dynamic property controls (e.g., animated counters), integrating real-time data from external APIs, and implementing sophisticated behavioral code overrides (such as scroll-triggered animations or magnetic interactions). Ideal for extending Framer's capabilities for professional web design.

This comprehensive 'Hello World' guide serves as a foundational tutorial for Framer development. It demonstrates key skills across the ecosystem, including building functional plugins (UI interaction), creating customizable code components with property controls, implementing dynamic code overrides for sophisticated animations, and interacting with the Framer Server API for headless site data management. Ideal for developers starting a new Framer integration or mastering core API patterns.

This guide provides comprehensive security best practices for developers building with Framer. It covers secure credential management (like API keys and Site IDs), implementing the principle of least privilege, and securing plugins and Server API connections. Use this when auditing your Framer setup or ensuring production-level security for sensitive data handling.

A comprehensive guide to implementing real-time data synchronization and handling event triggers with Framer's API. This skill covers subscribing to CMS changes via WebSockets, implementing secure external webhook endpoints with signature validation, and integrating Framer plugin event listeners for dynamic interaction. Use this when building complex, event-driven web applications connected to Framer.

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.

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 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 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.

This document outlines the reference architecture for integrating diverse enterprise knowledge sources (such as Confluence, Jira, Notion, and Slack) into the Glean search index. It details the end-to-end data flow, covering connector frameworks, message queuing, permission synchronization (ACLs), and client-side search APIs. Designed to ensure continuous, reliable, and low-latency unified search across all corporate data.