vetcoders-followup

To audit AI agent code for readiness, use a post-implementation audit skill that executes predefined checks like initialization and workflow context generation to synthesize implementation gaps and provide a GO/NO-GO verdict.

A post-implementation audit for agent-delivered work is a strict sequence of quality and security checks that identifies readiness risks, severity-ranked findings, and implementation gaps before deployment.

Run security and quality gate checks by executing delegated audits with tools like semgrep and cargo clippy to enforce code quality and surface vulnerabilities in the agent-generated implementation.

Yes, you can automate code review to identify implementation gaps by running a predefined sequence of workflow audits that synthesize findings into a consolidated verdict with severity-ranked findings.

Yes, the readiness check audit provides a clear deployment decision by synthesizing quality gate outcomes and readiness risks into a consolidated GO/NO-GO verdict for the agent-delivered work.

Perform a readiness check on agent workflows immediately after the AI agent implements a new feature and before manual testing to ensure no security vulnerabilities or implementation gaps reach deployment.