KYE Meaning Continuity Lab
Check whether meaning survives AI agent delegation
None defined yet.
KYE Protocol™ makes who/what acted, on whose authority, with what continuity of meaning, observable, governable, revocable and replayable across humans, AI agents, tools, workflows, APIs and autonomous services.
Most systems prove what happened. KYE also asks whether the meaning survived.
Every entity in KYE™ has a state. State drives what's allowed at runtime. Watch a vendor onboarding move through its lifecycle:
| Hugging Face artifact | What | License |
|---|---|---|
| meaning-continuity-lab | Interactive demo: 5 scenarios × 8 continuity dimensions → meaning-continuity score, drift reason codes, signed-style decision JSON | Apache-2.0 |
| schemas (coming) | All KYE™ JSON Schemas (Core, Continuity, Discoverability, Ontology, Operating Model, Assurance Card, Formal Rules, Action Admissibility, Meaning Continuity) | Apache-2.0 |
| reason-codes (coming) | Canonical reason-code dictionary across decisions, drift events, obligations | Apache-2.0 |
| examples (coming) | Validated example payloads for every schema | Apache-2.0 |
| conformance-fixtures (coming) | Conformance test vectors used by the runner | Apache-2.0 |
In agentic systems, an action's authorised meaning can drift before execution. Memory becomes stale, context changes, incentives conflict, intent gets reinterpreted across handoffs.
KYE Meaning Continuity™ checks whether original intent, constraints, context, memory, incentives, timing and state remain aligned across handoffs before the action is admitted, authorised, committed and evidenced.
Attribution proves who acted. Meaning Continuity™ checks whether the action still means what it was supposed to mean.