Skill UI

A comprehensive checklist for deploying Groq-powered applications to production. It covers critical areas including secure API key management, model fallback strategies, rate limit planning, implementing robust error handling (e.g., circuit breakers), setting up health endpoints, and configuring detailed monitoring and spending controls necessary for a successful, stable go-live.

This skill automates and configures robust Continuous Integration/Continuous Deployment (CI/CD) pipelines specifically for Guidewire applications. It handles the entire development lifecycle, including Gosu code compilation, running GUnit unit tests, building configuration packages, and deploying changes via the GCC API. It supports separating pipelines based on whether changes are in code or configurations.

This utility facilitates the end-to-end deployment of Guidewire integrations to the Cloud Platform. It manages the full release lifecycle, including building configuration packages using Gradle, uploading to the Guidewire Cloud Console (GCC), and promoting deployments through various environments (dev, staging, prod). It supports advanced features like zero-downtime releases and robust rollbacks.

Configures the Guidewire Studio local development environment, enabling efficient development, debugging, and testing. Features include Gosu debugging with breakpoints, hot deployment for rapid Gosu changes, GUnit integration for unit testing, and local test data loading via sample data loader. Ideal for simulating and developing the InsuranceSuite locally using 'gradle runServer'.

This skill automates the configuration and setup of Guidewire applications across multiple environments (Development, Staging, Production). It manages configuration promotion, handles environment-specific OAuth credentials, and sets up separate integration gateway endpoints. It ensures strict data isolation, streamlining the entire CI/CD deployment process for enterprise insurance systems.

This comprehensive checklist verifies the readiness of Guidewire Cloud for production deployment. It covers critical steps including Gosu compilation validation, GUnit test execution, API role configuration, integration gateway endpoint testing, batch process scheduling verification, and monitoring alert setup. It guides the promotion of configurations through dev, staging, and production environments via GCC.

This skill provides comprehensive guidance for the creation, organization, and management of Helm charts. It is essential for packaging, distributing, and deploying Kubernetes applications across various environments. Use it when implementing complex, templated, and reusable manifests for robust cloud-native deployments.

Provides calibration-free weight quantization for LLMs down to 1-bit precision with multiple optimized backends, ideal for fast deployments with vLLM/HuggingFace and LoRA/PEFT fine-tuning without collecting calibration data.

This comprehensive guide provides a multi-platform deployment solution for Ideogram-powered image generation APIs. It includes detailed code and setup steps for Vercel, Google Cloud Run, and self-hosted Docker containers. The solution addresses key production concerns, including secure secret management (API keys), handling generation timeouts, and ensuring generated images are persisted to durable cloud storage (like S3) with CDN integration for reliable service operation. Use this when migrating Ideogram prototypes to a production environment.

A comprehensive checklist and guide for deploying and maintaining Ideogram image generation services in a live production environment. It covers essential steps including API key management, request handling best practices, ensuring image persistence in durable storage, comprehensive error handling (401, 422, 429), and defining robust rollback procedures.

Automates inference latency profiler tasks in ML deployment scenarios, offering step-by-step guidance on model serving, MLOps pipelines, monitoring, and production optimization, generating production-ready code and validating outputs against best practices.

Detects fail-open insecure defaults such as hardcoded secrets, weak auth, or permissive security that allow production apps to run unsafely, guiding auditors through discovery, verification, confirmation, and reporting steps during security reviews or deployment validation.