Dynamic Future-Claim Certification: A Replayable Authority Validation Protocol with Canonical Artifacts

Dynamic Future-Claim Certification (DFCC) is a protocol for deciding when a bounded claim about the future may be asserted, denied, withheld, reused, weakened, transferred, blocked, or retired. The work addresses a practical problem shared by planning systems, controllers, monitoring tools, verification workflows, AI agents, and decision-support systems: future-facing statements can authorize actions, block actions, allocate resources, or become assumptions for other systems, yet their authority often depends on assumptions that may later change. DFCC does not aim to improve forecasting accuracy or replace probability, statistics, reachability analysis, model checking, runtime verification, or assurance cases. Instead, it provides a machine-checkable lifecycle layer above such methods. A future claim is evaluated only within an explicit assessment frame, accepted observations, admitted assumptions, finite horizon, dependency records, policy gates, and validation checks. The protocol separates issue-time certificates from recomputed status-time authority views, so a claim that was valid when issued can later be maintained, weakened, transferred, suspended, revoked, or recomputed when inputs, models, dependencies, policies, or evidence change. The framework emphasizes replayable and auditable claim use. It specifies canonical artifacts, manifest digests, schema validation, closed failure records, reason references, set references, wire-level records, conformance profiles, and golden test cases so that independent implementations can recompute the same authority status from the same admitted inputs. Its purpose is to make unsupported, stale, out-of-scope, or misframed future claims operationally visible rather than leaving them hidden inside plans, reports, simulations, or informal statements. This paper is intended for researchers and developers working on safe planning, AI agent governance, runtime assurance, formal verification, monitoring systems, software workflows, and decision systems that must manage claims about bounded futures under changing assumptions.