Skill UI

This skill defines the mandatory conventions and architectural rules for developing maintainable, cross-platform applications using Avalonia UI and the Zafiro toolkit. It enforces a functional-reactive MVVM approach, prioritizing explicit error handling via Result types, and mandates leveraging Zafiro's existing abstractions to ensure code quality and predictability.

Provides strategies to optimize costs when utilizing the Cohere API. This guide covers model tier selection (economy, standard, premium), implementing token budgets, reducing embedding storage costs (e.g., using int8), and establishing comprehensive usage trackers. It is essential for maintaining cost predictability in production AI deployments.

This tool analyzes historical sprint velocity data to generate a comprehensive engineering team health report. It moves beyond simple charts by diagnosing underlying delivery patterns, identifying risks like chronic over-commitment, and assessing story point calibration. The report provides actionable recommendations for improving capacity planning and team predictability.

This document provides a comprehensive guide to the principles and vocabulary needed to write high-quality, predictable, and effective skills. It covers advanced concepts like model-invoked vs. user-invoked skills, managing context load, structuring information hierarchies (steps vs. reference), and implementing progressive disclosure to improve agent predictability.