skill-gates

Automating AI agent skill loading involves mapping specific tool names to required skills using CLI commands. This rule-based system intercepts tool calls and conditionally injects the necessary skill context to prevent runtime errors.

To prevent runtime errors from missing tools, configure a controlled failure mechanism that intercepts shell commands and runtime tools. This resolves missing dependencies by conditionally injecting the required skill context into the active session.

Yes, you can define custom regex triggers for shell commands. Rule customization features allow you to specify custom matchers for tools, groups, or shell commands via regex or prefix patterns to override default agent behaviors.

You can list and disable default agent skill gates by using the provided CLI interface. This introspection feature enables you to manage, reset, or override default skill behaviors directly without performing manual JSON configuration edits.

Dynamic gate management is a lifecycle control method that automatically triggers skill loading when a specific tool is invoked. It ensures necessary runtime tools are loaded only when required, preventing errors and overriding default agent behaviors.

Yes, the ravi runtime supports conditional activation of agent skills. You can use the ravi skill-gates set command to map specific tool names to required skills, facilitating rule-based overrides and custom triggers for your agent workflow.