SMUAI Blog

Separate standards compliance, vendor compatibility, workflow quality, and runtime evidence with a ten-point Agent Skills audit designed for real engineering repositories.

Skill selection begins with metadata, not the hidden body. Learn the documented progressive-disclosure model and the observable evaluation method we use to improve routing.

The SKILL.md content format is portable, but discovery paths and runtime behavior differ. Use this vendor matrix and adapter strategy to avoid false one-setup claims.

Learn how Copilot, Codex, and Claude load repository instructions, and how we keep one source of truth while preserving tool-specific discovery paths.

Personas and skills are not interchangeable. Learn the separation we use between role, persistent repository rules, and task procedures—and where it is convention rather than standard.

Learn what the Agent Skills standard actually requires, what agents see during discovery, and the authoring practices we use to make workflows clear, safe, and testable.

A clean .github/ directory is the difference between agents that follow your standards and agents that guess. Here is the layout for skills, agents, and instructions — and the rules that keep each in its lane.

Agent Skills are reusable, folder-based capabilities that AI coding agents load on demand. Learn what the open SKILL.md standard is, how it works, and why it beats copy-pasting prompts across GitHub Copilot, Codex, and Claude.