Skill UI

This skill guide helps developers master best practices and architectural patterns for Godot 4 game development using GDScript. It thoroughly covers implementing game systems, managing complex state machines, utilizing signals, and optimizing performance. Use this when building robust, scalable, or advanced Godot games.

Collection of Go idioms and best practices for building robust, maintainable services, covering simplicity, zero values, interface returns, error handling, and concurrency when writing, reviewing, or refactoring Go code.

This skill guides you through designing and implementing production-grade Grafana dashboards for comprehensive system observability. Learn to visualize critical metrics, track key performance indicators (KPIs), monitor infrastructure health (using principles like RED/USE), and build actionable alerts using Prometheus data sources. Ideal for DevOps engineers and Site Reliability Engineers (SREs).

This skill provides comprehensive guidelines for monitoring Granola usage, tracking team meeting patterns, and building detailed analytics dashboards. It guides users in defining critical metrics (e.g., adoption rate, efficiency score) and establishing robust data pipelines. Users can stream meeting metadata from Granola to data warehouses like BigQuery, enabling deep, customizable reporting and automated weekly insights via services like Zapier and Slack.

This skill guides the design and implementation of complex GraphQL APIs. It specializes in schema design, utilizing Apollo Federation for distributed microservices, optimizing resolvers with DataLoader for N+1 prevention, and implementing real-time subscriptions. It covers security, complexity analysis, and adherence to best practices for building scalable, high-performance graph architectures.

Guidance for building robust GraphQL services: schema design with Relay-style pagination, resolver patterns that leverage per-request DataLoader for N+1 prevention, subscription handling, and structured error payloads to simplify client integrations.

Guides API developers through building well-structured GraphQL mutations with best-practice patterns, production-ready code, and validation help whenever “graphql mutation builder” appears in the request.

A comprehensive guide to implementing advanced LLM patterns using the Groq API. This workflow demonstrates how to handle chat completions, robust tool/function calling for integrating external services (like weather or search), and enforcing structured data output using JSON mode and strict schemas. Ideal for building real-time, production-grade AI features.

A comprehensive guide to using Groq's high-speed LPU for chat completion. This resource provides code examples in TypeScript and Python, covering basic chat interactions, streaming responses, and advanced multimodal features. Ideal for developers building high-performance, low-latency AI applications using the Groq API.

A comprehensive guide to setting up a fast, reproducible local development workflow for Groq applications. This setup includes structured project scaffolding, implementing singleton clients, defining model constants, and providing isolated unit tests with mocking, alongside live integration tests. Ideal for developers building low-latency LLM applications and ensuring rapid iteration cycles.

A comprehensive guide for migrating Large Language Model (LLM) integrations from providers like OpenAI or Anthropic to Groq. It details technical steps including SDK replacement, model ID mapping, building provider abstraction layers, and implementing zero-downtime traffic shifting using feature flags. This ensures developers can leverage Groq's superior speed while maintaining service continuity.

A comprehensive guide to building scalable, event-driven architectures using the Groq API. Learn advanced patterns including Server-Sent Events (SSE) for real-time streaming, batch processing with job queues (e.g., BullMQ), and processing incoming webhook events for robust LLM pipelines.