Skill UI

This guide provides advanced techniques to boost Framer API performance. It covers critical optimization areas including batch CMS syncing to prevent timeouts, memoizing expensive React components for better render performance, establishing persistent WebSocket connections, and optimizing image URLs before CMS synchronization. Use this when aiming to improve overall speed and stability of Framer-integrated applications.

A comprehensive checklist designed to guide users through deploying Framer integrations to a live production environment. It covers best practices for plugins, code components, server API synchronization (CMS), and final site publishing, ensuring a thorough and reliable go-live process.

Provides robust patterns for handling API rate limits, throttling, and connection errors when integrating with the Framer API. It covers implementing exponential backoff, retry mechanisms, batching large CMS writes, and debouncing plugin operations to ensure reliable and high-throughput API calls.

This skill provides a comprehensive guide for analyzing, planning, and executing upgrades of the Framer SDK, plugin API, and migrating between different Framer platform versions. It helps developers detect breaking changes, follow version checks, and manage common migration patterns required when updating the Framer environment.

A collection of production-ready patterns for integrating frontend applications with backend APIs. It solves complex asynchronous issues such as race conditions, stale data, and duplicate requests. Patterns include centralized API layering, request cancellation (AbortController), exponential backoff retries, debouncing, and request deduplication, ensuring highly resilient and reliable user experiences.

A powerful pre-tool-use hook designed to significantly improve AI-generated code quality and reliability. GateGuard forces the LLM to conduct concrete investigations—such as listing imports, checking data schemas, and identifying affected modules—before committing any edits, writing new files, or executing destructive commands. It moves beyond simple self-evaluation by demanding verifiable facts, dramatically reducing bugs and increasing design depth in complex coding workflows.

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.

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.