Agent Skills Hub

business-model-canvas

Business model design and analysis using the Business Model Canvas framework with 9 building blocks.

omc-plan

Intelligent strategic planning and requirements gathering with multi-perspective consensus loops and structured deliberation.

tdd-guide

Comprehensive Test Driven Development (TDD) assistant for engineering teams, featuring intelligent test generation, coverage analysis, and multi-framework support.

prompt-optimizer

Transforms vague or poorly structured prompts into optimized, high-performance instructions using proven prompt engineering principles for better AI model execution.

debugging

Standardized debugging and diagnostic guidelines for AI coding agents.

evaluation

Build systematic evaluation frameworks for AI agents using multi-dimensional rubrics, LLM-as-a-judge, and regression testing to measure performance, quality, and context engineering effectiveness.

ux-audit-walkthrough

Minimalist UX/Interaction Audit Expert that deconstructs complex interactions through cognitive load and operational efficiency lenses.

ring:testing-skills-with-subagents

A meta-skill for building robust AI agent skills using a TDD approach: define failure (RED), implement the skill (GREEN), and plug rationalization loopholes (REFACTOR).

deep-research

A systematic, multi-angle web research agent. Use for deep investigation, complex queries, and as a mandatory pre-research step before content generation to ensure evidence-backed, high-quality results.

legal-risk-assessment

Assess and classify legal risks using a severity-by-likelihood framework. Evaluate contract risk, deal exposure, and issue severity to determine if senior counsel or external review is required.

swiftui-performance-audit

Audit and optimize SwiftUI runtime performance. Diagnose slow rendering, janky scrolling, high resource usage, and layout thrash with code review, architecture analysis, and Instruments profiling guidance.

ai-writing-detection

Comprehensive AI-generated text detection framework. Features multi-layer analysis of vocabulary, structural patterns, model-specific fingerprints, and technical metadata artifacts to identify AI authorship.