Skill UI

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 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.

Modal Serverless GPU provides on‑demand, pay‑per‑second access to T4 through H200 GPUs, letting you deploy ML models as auto‑scaling APIs, run batch jobs, and prototype without managing infrastructure.

A comprehensive guide to selecting the optimal architecture for Replit applications. It compares three scaling models—single-file scripts (prototypes), modular apps (MVPs), and multi-service systems (large scale)—to help developers choose the correct database, storage, and deployment strategy as their project grows.

torchforge is Meta's advanced PyTorch-native library designed for agentic Reinforcement Learning (RL). It fundamentally separates core RL algorithms from complex distributed infrastructure concerns. This allows researchers to rapidly prototype and experiment with novel RL methods (like GRPO) using clean, PyTorch-native abstractions, while automatically handling large-scale tasks like distributed training across thousands of GPUs using Monarch and TorchTitan.

A specialized skill for building modern Vue 3 applications using pure JavaScript, completely avoiding TypeScript. It implements the Composition API, configures modern build tools like Vite, and ensures robust type safety by utilizing JSDoc annotations (@param, @returns, @typedef) instead of a compiler. Ideal for teams preferring vanilla JavaScript, migrating from Vue 2, or needing quick prototypes without a TS setup.

A specialized assistant designed to act as a senior software architect. It critiques code generated by AI tools or rapidly prototyped code, moving beyond simple syntax checks. The auditor identifies deep structural flaws, technical debt, architectural weaknesses, and production risks (e.g., security vulnerabilities, poor error handling, tight coupling) that make code fragile or unsuitable for deployment.

Helps product managers match hypotheses, risks, and resources to the right Proof of Life probe so they can pick the cheapest prototype that reveals the harsh truth before overbuilding.

This comprehensive guide outlines best practices for building reliable and robust AI agent harnesses. It covers optimizing action spaces, defining structured tools, managing observation formats, and implementing essential error recovery contracts. Use these principles to dramatically improve agent completion rates, manage context budgets effectively, and transition AI prototypes into stable, production-grade autonomous systems.

Comprehensive guide to LLM Operations (LLMOps). Covers advanced topics like Retrieval-Augmented Generation (RAG), vector database management (Pinecone, Chroma), embeddings, fine-tuning, prompt engineering, and cost optimization. Essential for bridging the gap between AI prototypes and reliable, scalable, production-grade AI systems.

A comprehensive 5-day, structured process (Map, Sketch, Decide, Prototype, Test) for rapidly testing and validating product ideas using real users. Developed by Google Ventures, this framework helps teams de-risk major product decisions by moving beyond endless debate to actionable, validated insights in a single week. Ideal for startups and established teams facing critical business challenges.

This skill guides the detection and exploitation of JavaScript prototype pollution vulnerabilities. It covers both client-side (DOM XSS) and server-side (RCE, Auth Bypass) attacks by injecting properties into Object.prototype using keys like `__proto__`. Use this when assessing APIs that deep-merge or clone user-controlled JSON data, or for general web application security testing.