Skill UI

This tool evaluates how thoroughly a feature implementation meets product requirements (PRDs) or specifications. It scores acceptance criteria case-by-case, independently grading both the code implementation and the associated test coverage (unit and E2E). Ideal for benchmarking multiple development efforts, auditing adherence to specifications, or determining if a feature is 100% complete and compliant with the ground truth PRD.

A comprehensive, adaptive framework for developing and implementing features, adhering to a strict, multi-phase workflow: Specify, Design, Tasks, and Execute. This skill ensures feature quality through granular task breakdown, atomic Git commits, requirement traceability, and mandatory, independent verification. It automatically adjusts its depth based on feature complexity (Small to Complex), providing a robust mechanism for managing technical debt and capturing project lessons.

This skill structures a highly controlled, bounded development life cycle for AI agents. It mandates a structured three-phase workflow: Planning (Spec), Implementation (Build), and Verification (Review). It is essential for building complex features from scratch, especially when dealing with ambiguous requirements, high risk, or needing explicit human approval gates to ensure the resulting code meets all defined specifications.

This tool enables web interaction using natural language descriptions instead of complex CSS selectors. By utilizing a specialized page-agent and an LLM-driven tool-call loop, users can simply state their goal (e.g., "Fill the search box with cats and submit"). It is ideal for dynamic web pages, ambiguous structures, or quick, one-shot interactions where robust selector writing is impractical. The system provides graceful degradation if the advanced page-agent is unavailable.

Automates the scaffolding of a complete Aggregate Root structure following Domain-Driven Design (DDD) principles. It generates necessary boilerplate files including the core entity, immutable value objects, repository interface, domain events, and unit test stubs within a specified bounded context. This tool is essential for modeling new business concepts or extending existing domain models while maintaining strong architectural integrity.

Hookify rules enable developers to define custom, event-driven workflows using Markdown files with YAML frontmatter. These rules monitor specific operational events (such as bash commands, file edits, or user prompts) and can trigger warnings or block operations when predefined regex patterns are matched. They are essential for enforcing coding standards, preventing dangerous operations, and guiding development adherence in complex software environments.

This skill helps transform vague product or engineering ideas into structured, verifiable acceptance criteria (AC). It is crucial for high-impact changes involving security, data migration, or external APIs. By inspecting existing context and asking minimal, targeted questions, it produces clear, observable criteria, significantly de-risking the development process and ensuring handoff readiness.