Better Agent Skills: Encoding Domain Knowledge and Rules for Reliable AI Coding Agents

AI agents can understand general technologies but often lack the project-specific business rules, architectural decisions, and past incident lessons needed to work correctly in a given codebase. The author argues that agent skills, reusable packages of instructions and resources, can fill this gap by turning domain knowledge into executable parts of an engineering process. A useful skill, built around a SKILL.md entry point, specifies authoritative data sources, required inputs, validation steps, and expected outputs rather than offering vague best-practice advice. The article contends that generic skills generated from a title alone add little value, since the real benefit comes from information a model cannot reliably infer. The guidance draws on the open Agent Skills format and illustrates the approach with a financial fund-analysis example.