Skill UI

Provides advanced search strategies and domain knowledge for football queries that fall outside the major European leagues (e.g., Premier League, La Liga). This guide covers critical contexts in African leagues (CAF, PSL), South Asian leagues (I-League, ISL), Russian football, and tracing players' origins, ensuring comprehensive and non-biased research on global football history and facts.

This coach is designed to systematically develop creative thinking and problem-solving skills. It guides users through established methodologies such as Design Thinking, SCAMPER, TRIZ, and Lateral Thinking. It teaches users how to move beyond initial ideas, overcome creative blocks, and apply structured frameworks to generate, refine, and implement novel solutions across various domains. Ideal for students, professionals, and entrepreneurs facing complex challenges.

The Hugging Face Transformers library is a comprehensive toolkit providing access to thousands of pre-trained models across diverse domains including Natural Language Processing (NLP), Computer Vision, Audio, and Multimodal tasks. It enables developers to easily load models, perform high-level inference (e.g., text generation, classification, QA), and fine-tune models on custom datasets using streamlined APIs like Pipelines and the Trainer class. Ideal for building advanced, state-of-the-art AI applications.

Provides technology-agnostic guidance for architecting and reviewing modular systems. This skill covers core architectural principles such as bounded contexts, state isolation, explicit contracts, and failure containment. Use it when determining service boundaries, assessing coupling between domains, or designing new greenfield architectures without assuming a specific framework, language, or repository structure.

This guide provides comprehensive steps to install and configure authentication for the BambooHR REST API. It utilizes HTTP Basic Authentication, requiring users to set up environment variables with their API key and company domain. The content includes setup instructions for Node.js and Python, along with full code examples for verifying a successful connection and retrieving employee directory data.

This advanced technique allows users to identify an obscure actor by linking indirect clues across three domains: the director, the film's characteristics, and the actor's biographical details. It is essential when direct searches fail, using the director's work or a film's context as the primary entry point to resolve the actor's identity.

This guide provides an expert framework for directory submissions, transforming them from simple listings into a foundational marketing layer. Learn how to strategically submit your SaaS or AI product to major directories (like Product Hunt, G2, and AI registries) to build high-authority backlinks, boost domain rating, and capture in-market buyer attention. It emphasizes building optimized destination pages (alternatives, use-cases) *before* submission to maximize lead conversion.

This skill acts as a rigorous, Socratic interviewer designed to stress-test a proposed plan against an established domain model and existing project documentation. It forces the user to sharpen terminology, resolve cross-cutting dependencies, and identify inconsistencies between stated requirements, code implementations, and documented decisions. It ensures the resulting architecture is precise, consistent, and well-documented by automatically updating the context and generating Architecture Decision Records (ADRs).

A universal infrastructure for automatically evolving and optimizing AI agents across any domain. Using LLM-driven mutation and iterative solve-observe-evolve cycles, it enhances critical components like prompts, skills, and memory by benchmarking performance against measurable datasets, enabling the creation of self-improving AI systems.

A comprehensive evaluation suite designed to benchmark the performance of Large Language Models (LLM) and Vision-Language Models (VLM) specifically for home security applications. It covers 143 diverse tests across 16 critical domains, including tool use, prompt injection resistance, contextual reasoning, alert triage, and detailed scene analysis, ensuring robustness for smart home AI systems.

This skill analyzes an existing codebase using domain context and architectural decisions to identify architectural friction and "deepening opportunities." It proposes refactored improvements to increase module depth, enhancing testability, improving maintainer locality, and making the codebase more navigable for AI tools. It focuses on transforming shallow modules into robust, deeply leveraged components.

This skill helps users create specialized 'steering documents' or project memory for highly specific domains (e.g., API standards, testing strategies, security patterns). By analyzing the existing codebase and following predefined architectural principles, it synthesizes concise, actionable guides that capture technical patterns, best practices, and domain-specific rules, ensuring project consistency and knowledge retention.