Skill UI

A systematic auditor designed to evaluate the resilience and quality of complex AI workflows. It scans across five critical dimensions—Prompt Quality, Context Efficiency, Tool Health, Architecture Fitness, and Safety—providing a scored report and prioritized, actionable remediation steps. Use this tool to find hidden flaws and ensure robustness before deploying any AI agent or system.

This catalog provides 11 core abstractions for implementing robust mailing functionalities within the Webiny API architecture. It includes Use Cases, Repositories, and various Event Handlers (e.g., before/after send, save). Developers should use these structured patterns to ensure their mailer logic is modular, highly testable, and follows industry best practices.

This skill guides the design and optimization of production-grade multi-agent systems. It specializes in using LangGraph, LangChain, and DeepAgents to create structured, complex AI workflows. It covers state management, agent routing, memory integration, and tool calling, making it ideal for building robust, scalable agents like supervisors, planners, and coders.

This comprehensive skill transforms raw game concepts into fully actionable, structured Unity development projects. It guides users through a five-phase pipeline, generating detailed Game Design Documents (GDDs), technical scene blueprints, core system architectures, and ready-to-use AI prompts for assets (3D models, textures, music, SFX). Ideal for concept validation and starting a complex game project from scratch.

A structured methodology for validating non-trivial decisions by subjecting them to an adversarial, fresh-context review. This process is crucial when correctness is paramount—such as in production, security-sensitive logic, or complex architecture—by forcing a skeptical examination that aims to disprove assumptions rather than simply approve them.

Diagnoses full-stack failure modes in agent and LLM applications, including wrapper regressions, memory contamination, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings and code-first fixes for production agent systems.

This comprehensive guide covers best practices for building modern Angular applications. It provides detailed instructions on component architecture, state management using Signals, advanced routing, dependency injection, handling forms (prioritizing Signal Forms), and implementing accessibility (ARIA). It also details setup procedures for new projects and modern rendering strategies like SSR.

A comprehensive framework for developing, defining, and maintaining a brand's core identity, voice, and market positioning. This skill guides users through foundational elements like Purpose, Vision, and Mission, provides structured positioning statement templates, and outlines brand architecture models (e.g., Branded House, House of Brands). It is essential for creating robust brand guidelines and ensuring consistent brand experience across all channels and touchpoints.

This comprehensive guide outlines expert strategies for creating high-authority competitor comparison and alternative pages. It details four proven formats—including 'Alternative to X,' 'You vs Competitor,' and 'Competitor A vs Competitor B'—to capture high-intent search traffic. By emphasizing honesty, deep research, and modular content architecture, these pages boost SEO ranking, build user trust, and drive qualified leads for sales enablement.

A rigorous, Chief AI Officer-level interrogation tool designed to pressure-test any plan involving artificial intelligence. Before deployment, it forces comprehensive review across crucial dimensions: evaluation metrics, hallucination risk, EU AI Act compliance, model architecture selection (API vs. build), cost economics, and required organizational roles. Essential for maintaining AI product safety and compliance.

Provides high-level strategic guidance for founders and Chief Data Officers (CDOs) in startups. This skill covers critical decisions such as AI training data rights and consent provenance, selecting optimal data architectures (warehouse, lakehouse, data mesh), valuing customer data as a strategic asset for M&A or fundraising, and planning data team organizational evolution. It focuses exclusively on strategic decision-making, not tactical engineering.