Skill UI

A comprehensive guide detailing the architectural standards, technology stack, file structure, and coding patterns for building modern, AI-driven full-stack applications. It covers best practices for Next.js, FastAPI, database interaction (Supabase), and structured AI integration (Claude), ensuring consistency and scalability across the development lifecycle.

The Witness toolkit provides cryptographic capabilities to sign, verify, and track documented code fixes (or 'markers') across multiple releases. It generates a signed manifest and a temporal history log, allowing users to precisely pinpoint the exact commit that introduced a regression, ensuring code stability in CI/CD pipelines.

This example demonstrates the structure of a blocked fixture within a testing framework. It serves as a placeholder to illustrate required missing elements, such as a detailed description, and is useful for understanding fixture setup requirements and testing methodology.

This skill reviews a single Markdown troubleshooting note to assess its clarity and completeness. It is designed to identify unclear steps, missing prerequisites, or unverifiable claims within a provided note. Use it when a user asks for feedback to improve an existing troubleshooting document. It provides concise, actionable rewrite suggestions without making any external changes or edits.

This example demonstrates unsafe or malicious review data inputs, specifically designed for calibration and security testing. It simulates prompt injection attacks and must only be used in controlled environments to validate secure data processing and system robustness.

This fixture provides a controlled environment for reviewing truncated packages. It is specifically designed for use during skill-reviewer calibration, ensuring that reviewers handle incomplete data sets correctly. Always refer to the comprehensive reference guide before making any decisions.

This skill is designed to review Chinese skill documentation to ensure it meets publishing standards. It systematically checks the clarity of descriptions and the executability of process steps, providing structured feedback in Chinese while maintaining necessary machine enumeration values for technical integrity.