AI Admissibility

AI Admissibility is an external admission boundary for AI-driven and automated execution. It is not a generic AI assistant, scanner, or observability tool. The core rule is simple: No Admission = No Execution. AI agents and automated workflows are increasingly able to deploy code, change infrastructure, call APIs, mutate customer data, grant access, or trigger security-sensitive operations. In those cases, logs and monitoring are too late: the important question is whether the action should be allowed to enter execution at all. AI Admissibility adds a fail-closed allow/deny decision surface before high-impact execution. A workflow or agent can propose an action, but execution should depend on an external admission decision rather than self-approval inside the same workflow. Key features: - external allow/deny admission before execution; - fail-closed behavior when admission is denied, missing, invalid, or unverifiable; - public proof/status surface; - GitHub Actions evaluation path; - technical brief and customer integration rule: No Admission = No Execution. It is designed for developers, DevOps teams, security teams, and AI agent builders evaluating controlled automation where production actions, infrastructure changes, access changes, or data mutations should not be self-authorized by the same system requesting execution.