Skill UI

A comprehensive guide to installing the flyctl CLI and setting up secure authentication for Fly.io edge compute deployments. This guide covers both interactive login and API token methods (User, Deploy, Org, Machines), which are essential for CI/CD pipelines and advanced resource management via the Machines API.

This guide walks users through verifying the complete setup of their Fondo account. It covers essential financial checks, including synchronizing bank transactions, reviewing automated transaction categorization (payroll, software, office), and confirming eligibility and data needed for R&D tax credits. Use this when initially setting up or auditing your core financial data flow.

This guide serves as a diagnostic reference for common Framer errors, covering issues across plugins, components, and Server APIs. It provides detailed causes and actionable fixes for problems like component rendering failures, incorrect API usage, and connection errors, helping developers efficiently debug and resolve integration issues.

This guide provides comprehensive instructions for setting up and authenticating Framer development environments. It covers two primary surfaces: the Plugin SDK (for UI running inside the editor) and the Server API (for headless CMS synchronization or CI/CD). Users will learn how to initialize projects, configure environment variables, and connect both client-side and server-side components.

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.

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.

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-action hook designed to enforce rigorous checks before AI agents modify code, create files, or execute destructive commands. Instead of relying on superficial self-evaluation, GateGuard forces the LLM to gather concrete facts (like dependencies, data schemas, and impacted modules), significantly improving code reliability and architectural depth. It provides multiple gates for edits, writes, and destructive bash commands.

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.

Configure comprehensive CI/CD pipelines for integrating Grammarly's text analysis into your development workflow. This setup uses GitHub Actions to run unit and integration tests on pull requests, validating API connectivity, enforcing content quality gates (e.g., minimum grammar scores), and ensuring documentation quality before merging to the main branch.

This comprehensive checklist guides developers through the necessary steps to deploy a robust and reliable Grammarly API integration in a production environment. It covers critical aspects such as secure credential storage, rate limit handling, implementing text chunking, designing error resilience patterns (circuit breakers, retries), and establishing comprehensive monitoring and alerting systems to ensure high content quality and system uptime.