Mechanism
Discovery integrity is the application of the integrity tracking mechanisms of the cognition architecture to the semantic discovery traversal process. Semantic discovery is the process by which a discovery object traverses the adaptive index through successive anchor evaluations to find, reason about, or synthesize information. During that traversal, the system tracks the semantic coherence of the traversal itself as a form of integrity monitoring. The same deviation detection, drift measurement, and corrective pressure mechanisms that operate on agent behavior operate on traversal behavior, because both are expressed as sequences of semantic mutations within the same governance framework.
The integrity disclosed here is not a property attached to a finished result, nor a set of checks a consumer runs against a producer's claims. It is a property of the traversal as it unfolds, computed step by step by the integrity engine as the discovery object moves through the index. The discovery object maintains a traversal integrity field that records the degree to which the traversal remains aligned with the original query intent.
The Traversal Integrity Field
The traversal integrity field is the structural component that carries discovery integrity through a traversal. It records the degree to which the traversal remains aligned with the original query intent, where that intent is the semantic vector established at traversal initialization. The field is maintained on the discovery object itself, so it travels with the object as the object descends through successive anchors rather than being reconstructed externally after the fact.
Because the traversal integrity field is part of the discovery object's carried state, the integrity record of a traversal is continuous with the agent-level integrity machinery described elsewhere in the same chapter. Traversal integrity is expressed in the same governance framework, recorded through the same lineage mechanisms, and consumed by the same confidence and forecasting primitives that consume agent behavioral integrity.
The Semantic Drift Metric
At each traversal step, the integrity engine computes a semantic drift metric. The semantic drift metric is a distance measure between the current traversal state and the original query intent. The current traversal state is the accumulated semantic content and context modifications of the discovery object, that is, everything the object has gathered and how its context has been modified as it has moved through the index. The original query intent is the semantic vector established when the traversal began.
The drift metric is evaluated step by step, not as a single end-of-traversal audit. Computing it at each step means the integrity engine observes the trajectory of divergence as it accumulates, rather than discovering after the traversal completes that the result no longer corresponds to what was asked. When the semantic drift metric exceeds a policy-defined threshold, the integrity engine records a traversal integrity violation, an event indicating that the traversal has diverged from its original purpose to a degree that may compromise the quality, relevance, or reliability of the traversal output.
Classes of Semantic Drift
The traversal integrity mechanism detects several classes of semantic drift that are relevant to search quality, reasoning reliability, and answer correctness. Topic drift is the condition in which the traversal has moved into semantic neighborhoods that are unrelated to the original query. Depth overrun is the condition in which the traversal has descended into increasingly specialized or tangential detail that, while semantically connected to the original query, has exceeded the appropriate scope.
Influence injection is the condition in which the traversal has been redirected by anchor content that is semantically attractive but irrelevant or misleading relative to the original intent. Circular traversal is the condition in which the traversal is revisiting semantic neighborhoods it has already explored without accumulating new relevant content. These four classes are named in the disclosure as the patterns the drift mechanism is designed to surface, each one a recognizable way in which a traversal can lose alignment with the query that initiated it.
Structural Consequences of a Violation
Traversal integrity violations produce the same structural consequences within the discovery context that behavioral integrity violations produce in the agent context. A violation drives confidence degradation that may trigger traversal pause and re-evaluation. It triggers forecasting activation that generates alternative traversal strategies. And it produces integrity logging that creates an auditable record of the semantic drift for subsequent quality analysis.
These are the same three consequences the integrity field produces at the agent level: confidence reduction that can suspend execution, forecasting that plans an alternative, and a lineage record of what occurred. Discovery integrity is not a separate enforcement apparatus bolted onto traversal; it is the agent-level coherence cycle operating on the traversal because the traversal is itself a sequence of semantic mutations within the same governance framework.
Responses to a Drift Violation
When a traversal integrity violation is recorded, the traversal may be handled in one of several disclosed ways. The traversal may be redirected back toward the original intent, correcting the divergence and resuming alignment with the query. It may be branched to explore the drift target as a secondary objective, treating the divergence as a candidate line of inquiry in its own right rather than simply discarding it. Or it may be terminated with a confidence-qualified result that discloses the integrity violation to the consuming entity.
The third option is significant: rather than returning a result that silently embeds the drift, the traversal can complete and surface the violation alongside a confidence qualification, so the entity consuming the result is told that drift occurred and how the result's reliability is affected. The divergence is disclosed as part of the output rather than hidden inside it.
Distinction From Conventional Retrieval
Conventional retrieval and multi-hop traversal treat a query as a one-shot match or a sequence of lookups, with no continuous account of whether the path taken still corresponds to what was asked. There is no carried record of alignment, and divergence, when it occurs, is invisible: the result is returned with opaque provenance, and a consumer has no structured signal that the traversal wandered. Where drift happens, it is silently absorbed into the answer.
The disclosed mechanism is distinguished by computing a semantic drift metric at every step against the original query intent, by carrying the resulting traversal integrity field on the discovery object, and by treating a threshold-exceeding divergence as a recorded violation that drives confidence, forecasting, and lineage consequences. Because the same deviation detection, drift measurement, and corrective pressure mechanisms operate on traversal behavior as on agent behavior, the integrity of a search is monitored with the same machinery that monitors the integrity of an agent's conduct, rather than being a best-effort property of an opaque retrieval pipeline.
Disclosure Scope
Integrity-modulated discovery traversal, comprising the traversal integrity field carried on the discovery object, the step-by-step computation of a semantic drift metric as a distance between the current traversal state and the original query intent, the recording of a traversal integrity violation when that metric exceeds a policy-defined threshold, the detection of topic drift, depth overrun, influence injection, and circular traversal, and the structural consequences of confidence degradation, forecasting activation, and integrity logging, is disclosed in the cognition filing (U.S. Application No. 19/647,395 and its international counterpart). This article describes that disclosed mechanism. The scope extends to embodiments in which the violated traversal is redirected toward the original intent, branched to explore the drift target as a secondary objective, or terminated with a confidence-qualified result that discloses the violation to the consuming entity, provided the drift measurement and corrective pressure mechanisms operating on traversal behavior remain those that operate on agent behavior within the same governance framework.
