meta-apply

To safely apply self-modification patches to a skill corpus, use a privileged landing gate that requires cross-model jury review and explicit human approval before executing any changes.

A cross-model jury review for skill patching is a safety mechanism where a separate model evaluates proposed changes before application. This ensures vetted modifications are safe prior to human authorization.

To apply an approved self-modification patch after human oversight, execute the privileged application command with the specific patch number to merge the vetted changes into the skill corpus.

Yes, human approval is required to execute privileged actions on staged patches. The system enforces this oversight layer to authorize and validate any corpus modifications before they are applied.

The primary limitation of automated skill corpus management is that it cannot bypass the designated landing gate. All self-modification patches require cross-model review and human intervention to authorize changes.

No, you cannot use this patching process without staging patches first. The system requires access to staged patches as a prerequisite to perform the cross-model review and apply the modifications.