Skill UI

A comprehensive, multi-stage checklist designed to ensure that any third-party or internal integration is robust, secure, and fully functional before being deployed to a live production environment. It covers critical areas including API security, error handling, performance optimization, monitoring setup, and disaster recovery planning.

This guide provides comprehensive techniques for managing API rate limits and ensuring reliable, high-volume API usage with Gamma. It covers methods such as reading rate limit headers, implementing exponential backoff for automatic retries, and building robust request queuing systems to handle throttling gracefully.

A comprehensive guide providing reference architectural patterns for building scalable, maintainable, and robust enterprise integrations involving Gamma services. It details three patterns—Basic, Service Layer, and Event-Driven—covering use cases from simple prototypes to high-volume, microservices-based systems, guiding system designers and architects on best practices.

This skill provides a comprehensive set of reusable, production-grade TypeScript patterns for interacting with the Gamma REST API, which lacks an official SDK. It includes implementation for typed clients, advanced polling mechanisms, structured error handling, and complex generation workflows (e.g., template-based generation). Use this when building robust, reliable applications that integrate deeply with Gamma's content generation services.

Provides comprehensive guidelines for securing API integrations with Gamma. Covers essential best practices such as using environment variables for API key storage, implementing key rotation strategies, request signing, and enforcing least privilege access control. Essential for developers building robust, production-grade applications.

A comprehensive, step-by-step guide detailing how to safely upgrade Gamma SDK versions (supporting both Node.js and Python) and migrate between different API versions. It covers checking current versions, reviewing changelogs, handling breaking changes in code patterns, and implementing thorough testing procedures to ensure a smooth deployment.

Gastown is a robust multi-agent orchestration system designed for Claude Code. It enables the simultaneous execution of multiple AI agents on complex projects. It manages the entire development lifecycle, from setting up workspaces and tracking work items (beads) to managing agent lifecycles (polecats/crew) and merging final code (Refinery). Use it when coordinating complex, parallel AI tasks.

Automates Gatling scenario creation for performance testing, offering guidance, production-ready code, validations and best-practice patterns for load, stress, and benchmarking workflows.

Automates GC log analyzer workflows for performance testing by guiding load, stress, benchmarking, and monitoring efforts with best-practice advice and ready-to-use configurations.

Guides building production-ready serverless apps on GCP with Cloud Run services and Functions, covering containerized APIs, event-driven Pub/Sub workflows, cold-start tuning, and deployment automation.

Generates complete, production-ready Google Cloud Platform (GCP) code examples and infrastructure templates. It spans various modern AI patterns, including ADK agents, Genkit RAG flows, and multimodal analysis using Vertex AI and Gemini. The output includes runnable code, deployment configuration (Terraform/IaC), security best practices (IAM, VPC-SC), and monitoring setup, ensuring enterprise-grade reliability and cost optimization.

Guides GCP users through GCS bucket configuration, offering best practices, configuration patterns, and production-ready snippets whenever someone asks about storage setup within Google Cloud.