Naming Conventions for Enterprise AI Agents
Consistent naming conventions are the difference between a Skills library that scales and one that breaks under its own complexity.
Why Naming Conventions Matter
Consistent naming conventions are the foundation of a scalable Skills library. Without them, different teams use different names for the same concepts, agents can't reliably find the Skills they need, and the library becomes unmaintainable as it grows.
Agent and Genie Naming
Use descriptive, role-based names: [Function] [Agent Type]. Examples: "HR Onboarding Assistant", "IT Support Agent", "Procurement Approval Agent". Avoid technical names that won't mean anything to end users or business owners.
Skill Naming
Skills use verb-noun format: [Action] [Object]. Examples: "Get Open Opportunities", "Create Purchase Request", "Approve Expense Report". The name should describe what the Skill does, not how it does it. Avoid abbreviations, system names, and technical jargon in Skill names.
Knowledge Base Naming
Knowledge Bases use descriptive noun phrases: [Subject] [Type]. Examples: "Procurement Policy Guide", "IT Security FAQ", "HR Benefits Reference". The name should make it obvious what the Knowledge Base contains.
Project and Folder Structure
Organize agents, Skills, and Knowledge Bases in folders by business function: HR, Finance, IT, Sales. Within each function, group by agent: "HR / Onboarding Agent / Skills", "HR / Onboarding Agent / Knowledge Bases". This structure makes it easy to understand what each project contains and who owns it.
Version Naming
Include version indicators for Skills that are undergoing active development: "Create Purchase Request v2 (Beta)". Remove version indicators from stable production Skills — version history is maintained by Workato's platform, not by the name.