Yakunashi-Safety Gate Connector for AI agents.

It forces the agent to list every fact it needs before it answers. If any of those facts are missing from your data, the agent is required to stop and tell you what's missing instead of guessing.

Yes. It is designed for high-stakes fields like medicine where missing a single variable, like kidney function, can make a confident answer dangerous. It ensures the agent flags these gaps.

Safe folding is a structured retreat. Instead of providing a potentially wrong answer, the agent provides a 'Beta-Ori' response that clearly identifies the missing data points needed to proceed.

It is ideal for engineering. It can be used to ensure that an agent doesn't approve a design without first verifying specific preconditions, like soil reports or load calculations.

It treats missing information as a hard stop. The agent is prohibited from speculating. It will provide a list of exactly what it needs to see to give you a reliable answer.

Yes, it works well for auditing. It can check for required regulatory markers and flag if any parts of the financial history are absent from the context provided.

The agent will immediately halt its response and trigger a folding message. It will explain that it detected a risk of speculation and list the specific data points it lacks.

Beta-Ori represents the tactical decision to remain silent or state what is missing rather than speculating. Safe folding triggers this state, outputting a precise checklist of missing parameters instead of an uncalibrated answer.

The capability audits the agent's confidence trace against the mapped evidence. If variables are missing but the agent claims high confidence, the safety gate flags it as yakunashi.

You do not need external files. Call the validate_yakunashi capability directly inside your agent loop before generating any answers to questions requiring data that may be missing.