Snapshot-Bound Admissibility Sequel: A Pre-Execution Specification for T₀-Based External Admission

This publication introduces Snapshot-Bound Admissibility Sequel, a non-operational specification artifact defining a snapshot-bound pre-execution admissibility class over an external carrier protocol layer. The specification defines a boundary-first admissibility regime in which execution may proceed only when admissibility has been externally grounded before action. For this class, lawful admissibility requires a strictly defined canonical basis time T₀, a valid snapshot relevant to T₀, a ruleset in force at T₀, deterministic derivation of the admissibility outcome from snapshot and ruleset, and a binary canonical outcome of ALLOW or DENY. If a valid snapshot basis at T₀ does not exist, execution is inadmissible. This artifact is non-operational. It does not publish an implementation, service interface, deployment method, credential path, payment path, or operational control mechanism. It is not a governance framework, not a post-failure truth layer, not a probabilistic scoring system, and not a discretionary review surface. The specification preserves the external-anchor law: without an external admission anchor, execution is structurally impossible in the canonical path, and refusal precedes execution. The central time law is: Admissibility belongs to T₀, not to the later machinery that transports, records, or applies it. Relation to existing boundary work: CRAB fixes the cloud-reference admission principle: system-significant cloud execution is inadmissible without an external admission anchor. SAB fixes the admission-entry boundary: an execution intent must first be admitted into the admissibility regime before a valid boundary request can exist. This sequel class defines the time-bound basis logic by which admissibility is grounded. License and use notice: This artifact is released under CC BY-NC-ND 4.0 It may be read, cited, linked, and referenced with attribution. No commercial use, modified versions, derivative specifications, operational claims, service claims, or implied endorsement are granted by this publication. No implementation, operational, commercial, licensing, evaluation, conformity, equivalence, endorsement, or authoritative interpretation rights are granted by this publication. Any such use requires separate written permission from the author. Licensing and interpretation framework: https://doi.org/10.5281/zenodo.18381146 Current clarification version: https://doi.org/10.5281/zenodo.19846720 Related public project surface:https://ai-admissibility.com/ This link is provided for public project context only and does not convert this reference artifact into an operational service, implementation, or commercial offer.