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TG-VRR-2

TrustGate Validation Rule Registry - 2


Part 6 — Rule Binding Model


131. Purpose

The Rule Binding Model defines how a canonical validation rule is connected to the artifacts, identifiers, engines, policies, evidence, and trust objects that it governs.

Where the Validation Binding Model defines the architectural domains to which validation may bind, the Rule Binding Model specifies the concrete bindings of an individual TG-VAL.

It answers the question:

"Exactly what does this validation rule validate?"

Every published validation rule shall declare its complete binding graph.


132. Binding Philosophy

A validation rule should never rely on implicit assumptions.

Everything required to execute, replay, audit, federate, or explain a rule shall be explicitly declared.

The Rule Binding Model ensures that every TG-VAL is:

  • self-describing;
  • machine-readable;
  • deterministic;
  • replayable;
  • explainable;
  • portable.

133. Rule Binding Object (TG-RBIND)

Every published validation rule shall have an associated Rule Binding Object.

The Rule Binding Object represents the complete set of relationships between a validation rule and the architectural artifacts it governs.

Example:

TG-VAL-000247



TG-RBIND

TG-RBIND is a canonical metadata object.

It contains no executable logic.


134. Rule Binding Identifier

Each Rule Binding Object receives its own identifier.

Format:

RBID-ZYZ-000001

Example:

RBID-ZYZ-000247

This identifier uniquely identifies a binding definition.

A new RBID is created whenever the binding graph changes.


135. Rule Binding Structure

Every Rule Binding Object shall contain:

FieldDescription
RBIDRule Binding Identifier
TG-VALValidation Rule
Rule VersionApplicable rule version
Binding VersionBinding version
Effective DateActivation timestamp
StatusDraft, Active, Deprecated, Retired
OwnerGovernance owner
Replay CompatibleBoolean
Federation CompatibleBoolean

136. Canonical Binding Categories

Bindings are organised into canonical categories.

CategoryPurpose
Identity BindingsCIA identifiers
Trust BindingsTrust Objects and Trust Vectors
Execution BindingsEngines and runtime
Governance BindingsPolicies and invariants
Evidence BindingsInput/output artifacts
Federation BindingsCross-ECO exchange
Replay BindingsReplay compatibility
Intelligence BindingsAI and TG-INTEL

Each category is independently governed.


137. Identity Bindings

Identity bindings connect a rule to the Canonical Identifier Architecture (CIA).

Supported identifiers include:

  • CMID
  • CSI
  • USO
  • CMI

Example:

TG-VAL



CSI


USO



CMID

Identity bindings define what canonical artifact is being validated, not where it is stored.


138. Metric Bindings (CMID)

Rules may validate one or more canonical metrics.

Examples include:

  • required metric exists;
  • metric datatype;
  • allowed range;
  • computational consistency;
  • reporting completeness.

Example:

TG-VAL-000142



CMID-ZYZ-000183
CMID-ZYZ-000442
CMID-ZYZ-000591

Metric bindings may reference:

  • single metrics;
  • metric groups;
  • metric families;
  • row-level CMIDs.

139. Signal Bindings (CSI)

Signal bindings specify the canonical signal definitions required by the rule.

Bindings may define:

  • required signals;
  • optional signals;
  • produced signals;
  • derived signals.

Example:

CSI



Invoice Signal



Emission Signal



Supplier Signal

Rules consume CSI—not raw payload formats.


140. Runtime Signal Bindings (USO)

Runtime bindings connect validation to individual signal instances.

Example:

USO



Runtime Signal



Validation

USO bindings provide:

  • lineage;
  • replay reconstruction;
  • duplicate detection;
  • execution traceability.

141. Trust Object Bindings (TOID)

Rules may validate Trust Objects.

Typical bindings include:

  • Trust State;
  • lifecycle;
  • ownership;
  • evidence completeness;
  • operational flags.

Example:

TOID



TG-VAL

142. Trust Vector Bindings (TVID)

Rules may evaluate one or more Trust Vector dimensions.

Examples:

  • Integrity
  • Authenticity
  • Completeness
  • Consistency
  • Timeliness
  • Provenance
  • Confidence
  • Federation Readiness

A rule may contribute to one or several Trust Vector dimensions simultaneously.


143. Trust Intelligence Bindings (TG-INTEL)

Rules may generate intelligence candidates.

Bindings define:

  • anomaly detection;
  • recommendation generation;
  • optimisation opportunities;
  • drift detection.

Rules never write TG-INTEL directly.

They emit intelligence candidates for governance review.


144. Invariant Bindings (INVID)

Every constitutional validation rule should bind to one or more CIR invariants.

Example:

INVID



TG-VAL

Bindings specify:

  • invariant;
  • enforcement level;
  • constitutional impact;
  • violation severity.

145. Engine Bindings (EID)

Rules declare which major engine owns orchestration.

Examples:

EID-TRUSTGATE

EID-VERA

EID-ZARA

EID identifies architectural ownership.


146. Micro-Engine Bindings (MEID)

Rules bind to executable Micro-Engines.

Example:

TG-VAL



MEID-VERIFY-CSI



MEID-CHECK-CMID



MEID-VERIFY-TOID

Multiple MEIDs may satisfy a single validation rule.


147. Managed Component Bindings (CMI)

Rules reference executable implementations.

Example:

TG-VAL



CMI



Implementation

CMI bindings preserve implementation lineage.


148. Execution Bindings

Execution bindings define runtime behaviour.

Typical bindings include:

  • execution mode;
  • scheduler policy;
  • timeout policy;
  • retry policy;
  • priority;
  • concurrency profile.

These bindings are interpreted by the Scheduler.


149. Validation Plan Bindings (VPLAN)

Rules may participate in multiple Validation Plans.

Example:

TG-VAL



Supplier Assessment



CSRD Report



ESRS Validation



Federation Export

Plans determine execution context.


150. Dependency Bindings (VCHAIN)

Dependency bindings specify execution order.

Example:

Schema Validation



Identity Validation



Trust Validation



Federation Validation

Dependencies shall remain acyclic.


151. Configuration Bindings

Rules may bind to runtime configuration parameters.

Examples:

  • thresholds;
  • feature flags;
  • retry limits;
  • warning levels;
  • execution profiles.

Configuration is resolved dynamically without changing rule identity.


152. Policy Bindings

Rules may reference policy artifacts.

Examples:

  • CSRD;
  • ESRS;
  • ISSB;
  • GRI;
  • Internal Policy;
  • Tenant Policy;
  • Federation Policy.

Policy bindings determine applicability.


153. Evidence Bindings

Rules define required evidence.

Evidence may include:

  • documents;
  • signals;
  • calculations;
  • signatures;
  • attestations;
  • provenance records.

Evidence bindings specify:

  • mandatory evidence;
  • optional evidence;
  • acceptable alternatives.

154. Result Bindings

Rules define produced validation artifacts.

Examples include:

  • TG-VRES;
  • TG-VEVID;
  • Trust Decision;
  • Operational Trust Flag;
  • TG-INTEL Candidate.

Every execution shall produce deterministic outputs.


155. Replay Bindings

Replay bindings define:

  • replay requirements;
  • historical version resolution;
  • deterministic execution guarantees;
  • replay exclusions.

Replay shall preserve original bindings.


156. Federation Bindings

Rules declare federation compatibility.

Bindings define:

  • exportability;
  • trust propagation;
  • evidence packages;
  • federation profile compatibility;
  • confidentiality level.

Internal execution metadata need not be exported.


157. DAL Bindings

Rules may determine ledger eligibility.

Bindings specify:

  • anchoring requirements;
  • signature validation;
  • completeness checks;
  • trust thresholds.

DAL anchoring shall only occur after successful validation.


158. Security Bindings

Rules may require security controls.

Examples:

  • digital signatures;
  • DID verification;
  • certificate validation;
  • encryption requirements;
  • key provenance.

Security bindings are evaluated prior to trust computation.


159. AI Bindings

Rules expose metadata for DSAIL.

Bindings include:

  • learning eligibility;
  • explainability level;
  • optimisation candidates;
  • confidence reporting;
  • drift monitoring.

AI recommendations never modify published rules.


160. Explainability Bindings

Every rule shall expose explainability metadata.

Including:

  • purpose;
  • rationale;
  • evaluated invariants;
  • evidence references;
  • remediation guidance;
  • constitutional impact.

Explainability bindings support:

  • audit;
  • dashboards;
  • federation;
  • AI.

161. Binding Resolution Order

During execution TrustGate resolves bindings in a deterministic sequence.

TG-VAL



Rule Binding



Configuration



Policy



Identity



Trust



Execution



Evidence



Replay



Federation



AI

Every replay shall resolve the identical binding sequence.


162. Binding Graph

A Rule Binding Object forms a canonical graph.

                 TG-VAL

┌──────────────┼──────────────┐
▼ ▼ ▼
INVID CMID CSI
│ │ │
▼ ▼ ▼
TOID TVID USO
│ │ │
└──────────────┼──────────────┘

TG-RBIND

┌─────────────┼──────────────┐
▼ ▼ ▼
EID MEID CMI
│ │ │
└─────────────┼──────────────┘

Scheduler


VRID

This graph is replayable, queryable, and fully traceable.


163. Binding Invariants

TVRR-RBIND-001

Every published validation rule shall possess exactly one active Rule Binding Object.


TVRR-RBIND-002

Rule bindings shall reference only canonical identifiers.


TVRR-RBIND-003

Bindings shall be immutable within a published version.


TVRR-RBIND-004

Binding graphs shall remain acyclic.


TVRR-RBIND-005

Replay shall resolve historical bindings exactly as originally executed.


TVRR-RBIND-006

Every constitutional rule shall reference one or more CIR invariants.


TVRR-RBIND-007

Every executable rule shall reference at least one MEID.


TVRR-RBIND-008

Every replay-critical rule shall reference one or more CMIs.


TVRR-RBIND-009

Every production rule shall expose explainability bindings.


164. Relationship to the ZAYAZ Architecture

The Rule Binding Model is the connective tissue between the Validation Rule Registry and the rest of the platform.

It integrates directly with:

ComponentRelationship
Canonical Identifier Architecture (CIA)Canonical identity bindings (CMID, CSI, USO, CMI)
Canonical Invariant Registry (CIR)Constitutional invariant bindings (INVID)
TrustGate Trust ModelTrust Object, Trust Vector, and TG-INTEL bindings
TrustGate Scheduler / Orchestrator EngineExecution planning and orchestration
Runtime Configuration EngineDynamic configuration and policy resolution
Replay SpecificationHistorical binding reconstruction
Federation ProfilesCross-ECO trust exchange
Distributed Assurance Ledger (DAL)Assurance anchoring eligibility
DSAILLearning, explainability, and optimisation

165. Summary

The Rule Binding Model transforms a validation rule from an isolated executable artifact into a fully governed architectural contract.

By introducing the Rule Binding Object (TG-RBIND) and the Rule Binding Identifier (RBID), every TG-VAL explicitly declares its relationships to canonical identifiers, trust artifacts, engines, runtime execution, replay, federation, governance, and AI. This explicit binding graph ensures deterministic execution, complete traceability, replay fidelity, and long-term architectural integrity across the ZAYAZ platform.


Part 7 — Validation Orchestration Model


166. Purpose

The Validation Orchestration Model defines how canonical validation rules are assembled into executable validation workflows.

Where the Validation Rule Model defines individual validation rules, and the Runtime Validation Model defines individual executions (VRIDs), the Orchestration Model defines how multiple rules cooperate to evaluate an artifact, workflow, report, or transaction.

The orchestration layer is responsible for transforming a collection of independent validation rules into a deterministic, dependency-aware execution graph.


167. Architectural Role

The Validation Orchestration Model sits between the Validation Rule Registry and the TrustGate Scheduler / Orchestrator Engine.

Validation Rule Registry


Validation Binding Model


Validation Orchestration Model


Scheduler / Orchestrator Engine


Runtime Validation Engine


Validation Results

This separation allows orchestration logic to evolve independently of rule definitions.


168. Core Runtime Objects

The orchestration layer introduces two canonical runtime artifacts.

ArtifactPurpose
TG-VPLANValidation Execution Plan
TG-VCHAINValidation Dependency Chain

These artifacts are runtime planning objects.

They do not replace TG-VAL or VRID.

Instead they coordinate them.


169. Validation Execution Plan (TG-VPLAN)

A Validation Execution Plan represents the complete validation strategy for a runtime operation.

Example:

Invoice Import



TG-VPLAN



Execute 87 validation rules



Produce Validation Report

Every execution plan is immutable after creation.


170. TG-VPLAN Identifier

Every Validation Execution Plan receives a canonical identifier.

Example:

VPLAN-ZYZ-20260704-000001

The identifier uniquely represents the execution plan.

It is independent from:

  • TG-VAL
  • VRID
  • TOID
  • TVID

171. Validation Plan Structure

A Validation Execution Plan shall contain:

FieldDescription
VPLAN IDUnique execution plan
NameHuman-readable name
PurposeBusiness purpose
Artifact TypePrimary artifact being validated
Applicable PolicyGoverning policy
Rule CountNumber of TG-VAL entries
Dependency GraphValidation ordering
Scheduler MetadataScheduling preferences
Execution StrategySequential, parallel, hybrid
Replay SupportReplay compatibility
Federation EligibilityExportability

172. Validation Dependency Chain (TG-VCHAIN)

Validation rarely consists of isolated rule executions.

Many rules depend on earlier validation results.

TG-VCHAIN represents these ordered dependency relationships.

Example:

Verify Schema



Verify Identity



Verify Trust Object



Verify Trust Vector



Verify Federation Eligibility



Verify DAL Readiness

173. TG-VCHAIN Identifier

Every dependency chain shall possess a canonical identifier.

Example:

VCHAIN-ZYZ-000104

Dependency chains may be reused across multiple execution plans.


174. Dependency Graph Model

Validation chains form a Directed Acyclic Graph (DAG).

          Schema
/ \
▼ ▼
Identity Metadata
\ /
▼ ▼
Trust Object


Trust Vector


Trust Decision

Circular dependencies are prohibited.


175. Dependency Resolution

Before execution begins, TrustGate resolves:

  • rule prerequisites;
  • artifact availability;
  • CSI dependencies;
  • Trust Objects;
  • Trust Vectors;
  • configuration;
  • federation requirements;
  • replay context.

Only resolved graphs may execute.


176. Execution Strategies

Execution Plans may specify one of several execution strategies.

StrategyDescription
SequentialStrict execution order
ParallelIndependent rules execute concurrently
HybridCombination of sequential and parallel execution
Event-DrivenTriggered by runtime events
IncrementalExecute only affected rules
ReplayHistorical reconstruction
SimulationNon-persistent execution

177. Scheduler Integration

Execution Plans are submitted to the TrustGate Scheduler / Orchestrator Engine.

The scheduler is responsible for:

  • queue management;
  • workload balancing;
  • dependency resolution;
  • retry scheduling;
  • prioritisation;
  • concurrency management;
  • timeout handling.

The Validation Rule Registry never directly invokes execution.


178. Execution Phases

Every execution plan progresses through defined phases.

Plan Created



Dependency Resolution



Scheduling



Resource Allocation



Execution



Aggregation



Trust Assessment



Persistence



Replay Registration



Completion

Each phase generates telemetry.


179. Rule Selection

Not every TG-VAL executes every time.

Rule selection considers:

  • artifact type;
  • tenant;
  • framework;
  • policy;
  • Trust Object state;
  • federation profile;
  • execution mode;
  • feature flags.

Selection shall be deterministic.


180. Conditional Execution

Rules may define conditional predicates.

Example:

IF

Country = EU

THEN

Execute CSRD Rule Set

Conditions are resolved before scheduling.


181. Dynamic Expansion

Execution Plans may expand dynamically.

Example:

Supplier Assessment



Supplier Category



Additional Validation Rules



Continue Execution

Dynamic expansion shall preserve replay determinism.

Expansion decisions become part of the replay record.


182. Execution Context Inheritance

Every VRID inherits execution context from the parent Validation Plan.

Inherited metadata includes:

  • execution policy;
  • scheduler context;
  • federation profile;
  • configuration snapshot;
  • replay session;
  • orchestration identifier.

This reduces duplication while preserving lineage.


183. Aggregated Outcomes

Execution Plans aggregate results across multiple validations.

Possible aggregate outcomes include:

ResultMeaning
PassedAll required rules succeeded
Passed with WarningsMandatory rules passed
FailedOne or more mandatory rules failed
InconclusiveRequired evidence missing
CancelledExecution terminated
PartialIncomplete execution

Aggregate outcomes feed the Trust Model.


184. Trust Integration

Validation Plans contribute evidence to:

  • Trust Objects;
  • Trust Vectors;
  • Operational Trust Flags;
  • Trust Decisions;
  • TG-INTEL.

Plans do not compute trust directly.

They generate canonical evidence consumed by the Trust Model.


185. Replay Integration

Replay reconstructs:

  • Validation Plan;
  • Dependency Graph;
  • Scheduler Decisions;
  • Rule Selection;
  • VRIDs;
  • Results;
  • Telemetry.

Replay shall preserve execution ordering exactly.


186. Federation Integration

Federation exchanges orchestration outcomes—not execution graphs.

Shared information may include:

  • validation summary;
  • evidence package;
  • attestations;
  • Trust Vector;
  • federation decision.

Internal orchestration remains local unless explicitly exported.


187. AI Integration

DSAIL analyses Validation Plans to identify:

  • inefficient execution paths;
  • redundant rules;
  • dependency optimisation;
  • scheduling improvements;
  • replay bottlenecks;
  • trust prediction.

AI recommendations shall generate TG-INTEL artifacts.

Execution Plans remain governance-controlled.


188. Telemetry

Every Validation Plan emits orchestration telemetry.

Typical events include:

  • plan created;
  • dependency resolved;
  • execution started;
  • execution completed;
  • retries;
  • failures;
  • aggregation complete;
  • replay initiated.

Telemetry integrates with:

  • Runtime Observability Engine;
  • Trust Intelligence;
  • Replay;
  • Scheduler.

189. Performance Metrics

Execution Plans maintain operational metrics.

Examples:

  • execution duration;
  • dependency resolution time;
  • queue latency;
  • scheduler wait time;
  • parallel execution ratio;
  • retry frequency;
  • rule throughput;
  • success rate.

Metrics support runtime optimisation.


190. Failure Recovery

Execution Plans define recovery policies.

Examples:

  • retry failed branch;
  • continue with warning;
  • abort execution;
  • quarantine artifact;
  • request manual review;
  • rollback trust update.

Recovery strategy is policy-driven.


191. Deterministic Execution

Execution Plans shall remain deterministic.

Given identical:

  • TG-VAL versions;
  • configuration;
  • evidence;
  • policies;
  • scheduler rules;
  • dependency graph;

the execution shall produce identical outcomes.


192. Orchestration Invariants


TVRR-ORCH-001

Every Validation Plan shall possess exactly one VPLAN identifier.


TVRR-ORCH-002

Every Dependency Chain shall possess exactly one VCHAIN identifier.


TVRR-ORCH-003

Execution graphs shall be acyclic.


TVRR-ORCH-004

Dependency resolution shall complete before execution begins.


TVRR-ORCH-005

Every VRID shall belong to exactly one Validation Plan.


TVRR-ORCH-006

Every execution plan shall preserve replay compatibility.


TVRR-ORCH-007

Execution strategies shall be explicitly declared.


TVRR-ORCH-008

Scheduler decisions shall be observable through telemetry.


TVRR-ORCH-009

Validation Plans shall never alter TG-VAL definitions.


193. Relationship to the ZAYAZ Architecture

The Validation Orchestration Model integrates directly with:

ComponentRelationship
TrustGate Scheduler / Orchestrator EngineExecutes VPLANs
Runtime Configuration EngineResolves execution policies
Runtime Observability EngineCollects orchestration telemetry
Trust ModelConsumes aggregated validation evidence
Replay SpecificationReconstructs execution plans
Federation ProfilesControls cross-ECO validation exchange
DSAILLearns from execution behaviour
DALReceives validated assurance outcomes
CIRGoverns invariant enforcement
CIAMaintains canonical identifier lineage

194. Summary

The Validation Orchestration Model elevates validation from isolated rule execution to governed, dependency-aware workflows.

By introducing TG-VPLAN (Validation Execution Plan) and TG-VCHAIN (Validation Dependency Chain), TrustGate gains a canonical orchestration layer that bridges the Validation Rule Registry with the Scheduler / Orchestrator Engine. This enables deterministic execution planning, dependency resolution, replay fidelity, telemetry, federation, and AI-assisted optimisation while preserving the immutability and governance of individual TG-VAL definitions.


Part 8 — Validation Result Model

Canonical validation results, evidence, verdicts, and runtime assurance artifacts for the TrustGate Validation Rule Registry.


195. Purpose

The Validation Result Model defines the canonical output produced by the execution of validation rules.

Every execution of a validation rule produces one or more immutable result artifacts that collectively document:

  • what was validated;
  • how it was evaluated;
  • which evidence was considered;
  • what decision was reached;
  • why the decision was reached.

The Validation Result Model forms the authoritative runtime evidence layer of TrustGate.


196. Core Runtime Artifacts

The Validation Result Model introduces two primary canonical runtime artifacts.

ArtifactPurpose
TG-VRESValidation Result
TG-VEVIDValidation Evidence Package

TG-VRES represents the outcome.

TG-VEVID represents the supporting evidence.


197. Validation Result (TG-VRES)

A Validation Result represents the outcome of executing exactly one TG-VAL.

Relationship:

TG-VAL



VRID



TG-VRES

Each TG-VRES is immutable once persisted.


198. Validation Result Identifier

Every Validation Result receives a unique identifier.

Example:

VRES-ZYZ-000001

Identifiers are globally unique.


199. Validation Result Structure

Every TG-VRES shall contain:

FieldDescription
VRES IDValidation Result Identifier
VRIDRuntime execution
TG-VALValidation Rule
Rule VersionVersion evaluated
Execution TimestampUTC
VerdictPass / Warning / Fail
ConfidenceNumeric confidence score
SeverityInformational → Critical
Replay CompatibleBoolean
ExplainabilityReference
Evidence PackageTG-VEVID
Trust ImpactTrust contribution

200. Validation Evidence Package (TG-VEVID)

Every Validation Result references an immutable evidence package.

Example:

TG-VRES



TG-VEVID



Signals
Documents
Calculations
Signatures
Attestations

Evidence is never embedded inside the validation result.


201. TG-VEVID Identifier

Example:

VEVID-ZYZ-000001

Evidence identifiers remain stable for replay.


202. Evidence Categories

Evidence may include:

CategoryExamples
Canonical SignalsCSI / USO
MetricsCMID
DocumentsUploaded evidence
Trust ObjectsTOID
Trust VectorsTVID
PoliciesPolicy IDs
Replay MetadataReplay IDs
Federation EvidenceAttestations
Cryptographic ProofSignatures

203. Validation Verdicts

TrustGate defines the following canonical verdicts.

VerdictMeaning
PASSValidation satisfied
WARNINGMinor deviation
FAILMandatory condition violated
INCONCLUSIVEInsufficient evidence
SKIPPEDRule intentionally not executed
ERRORValidation engine failure

204. Severity Levels

Every result carries a severity.

LevelMeaning
InformationalNo operational impact
LowMinor deviation
MediumReview recommended
HighSignificant issue
CriticalImmediate action required

Severity and verdict are independent concepts.


205. Confidence Assessment

Each result includes a confidence value indicating the reliability of the validation outcome.

Confidence may be influenced by:

  • evidence quality;
  • provenance;
  • signal completeness;
  • cryptographic verification;
  • replay consistency.

Confidence contributes to the Trust Vector but does not replace it.


206. Explainability

Every validation result shall expose an explanation.

The explanation shall include:

  • evaluated rule;
  • evidence used;
  • invariant references;
  • decision rationale;
  • remediation guidance.

Explainability shall be both machine-readable and human-readable.


207. Trust Impact

Validation results contribute evidence to the Trust Model.

A TG-VRES may:

  • increase trust;
  • decrease trust;
  • leave trust unchanged;
  • trigger operational flags;
  • generate TG-INTEL candidates.

The result itself does not compute trust.


208. Replay Compatibility

Every TG-VRES shall support deterministic replay.

Replay requires preservation of:

  • TG-VAL version;
  • RBID;
  • VRID;
  • evidence package;
  • execution context;
  • verdict.

209. Federation Compatibility

Validation results may be exchanged across ECO boundaries.

Federation exchanges:

  • verdict;
  • evidence references;
  • attestations;
  • trust contribution.

Internal execution details remain local unless explicitly permitted.


210. AI Integration

DSAIL analyses validation results to identify:

  • recurring failures;
  • anomalous behaviour;
  • evidence gaps;
  • optimisation opportunities;
  • predictive risks.

AI outputs are recorded as TG-INTEL artifacts.


211. Lifecycle

Validation results progress through a controlled lifecycle.

Created



Verified



Persisted



Referenced



Replayed



Archived

Results are never modified after persistence.


212. Validation Result Invariants

TVRR-VRES-001

Every VRID shall produce exactly one TG-VRES.

TVRR-VRES-002

Every TG-VRES shall reference exactly one TG-VEVID.

TVRR-VRES-003

Validation results shall be immutable.

TVRR-VRES-004

Evidence packages shall remain replayable.

TVRR-VRES-005

Validation verdicts shall be deterministic for identical inputs.

TVRR-VRES-006

Every production validation result shall expose explainability metadata.


213. Relationship to the ZAYAZ Architecture

The Validation Result Model integrates directly with:

ComponentRelationship
Trust ModelProvides trust evidence
CIRRecords invariant compliance
CIAMaintains canonical identifier lineage
Replay SpecificationReconstructs historical validation
Federation ProfilesExchanges validation evidence
DALAnchors assurance outcomes
DSAILLearns from validation results

214. Summary

The Validation Result Model establishes TG-VRES and TG-VEVID as the canonical runtime evidence artifacts of TrustGate.

By separating validation outcomes from supporting evidence, the model ensures immutability, explainability, replay fidelity, federation compatibility, and seamless integration with the Trust Model, Canonical Identifier Architecture, Canonical Invariant Registry, DAL, and DSAIL.




GitHub RepoRequest for Change (RFC)