Skill UI

This skill provides a comprehensive guide to designing and developing autonomous AI agents for code plugins. It covers the required file structure (YAML frontmatter), best practices for defining agent roles, designing robust system prompts, and setting up clear triggering conditions. Use this when you need to conceptualize, structure, or refine an agent's capabilities to handle complex, multi-step tasks autonomously.

Refines prompt files by analyzing prior successful patterns, improving structure, wording, and clarity while preserving the original intent and markdown front matter.

A comprehensive meta-skill template designed for developers to scaffold, structure, and define specialized Agent Skills for AI platforms like GitHub Copilot. It guides users through mandatory requirements, including folder naming conventions, YAML frontmatter best practices (name, description), and structuring the skill body with detailed workflows and documentation sections. Use this when building complex, specialized AI capabilities.

A comprehensive audit guide for submitting academic papers to the FAccT conference. It details critical, multi-step processes, including the mandatory abstract registration gate, maintaining mutual anonymity, adhering to strict ACM formatting rules, and including required endmatter statements (such as the Generative AI Usage Statement).

An advanced AI co-counsel designed for family and divorce law attorneys. This scaffold assists with the entire matter lifecycle—from intake and financial disclosure to drafting, mediation, and court preparation. It supports structural analysis, document organization, and strategy, while maintaining strict ethical boundaries and emphasizing attorney oversight. It is designed to be jurisdiction-agnostic, handling various personal-status regimes.

This workflow mandates external verification for all non-trivial factual claims, ensuring accuracy in high-stakes domains. It is essential when researching current events, legal matters, scientific claims, or providing statistics. The process requires decomposing tasks, searching external sources, and providing immediate, inline citations to support every claim, overriding reliance on internal, potentially outdated knowledge.