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Applicability logic

Explain when a policy or rubric should be used for a case, output, or coverage segment.

Applicability logic

Definition

Applicability logic is the boundary that decides whether a policy or rubric should be considered for a specific case, output, or coverage segment. It prevents a good standard from being applied to the wrong behavior.

Use this reference when a benchmark result is hard to explain because a standard seems relevant in some cases but not others. The question is not only whether the policy is correct; it is whether the policy was eligible to judge that output.

Fields, states, or lifecycle rules

  • Applicability sits between the case/output and the policy/rubric that may judge it.
  • Weak applicability makes benchmark failures noisy: a candidate can fail a good rubric on a case where the rule should not have applied.
  • Strong applicability names the behavior condition, source context, or case segment that brings the standard into scope.
  • Applicability changes can make old benchmark evidence stale because the same output may be judged by a different standard boundary.
  • This page explains the public object relationship, not a public rule language, API schema, or export contract.

Applicability logic should be read with Policies, Rubrics, Cases, and Coverage Dimensions. Use the Correctness Governance workflow to write the boundary and troubleshooting when the observed Case set is wrong.

Worked example

Applicability logic boundary

01

Start

Behavior input

Raw case
A user asks whether a product works with equipment they already own.
02

Middle

Judgment into standard

Policy
Compatibility claims require explicit source support.
Applicability logic
The policy applies only when the answer recommends, validates, or compares a product for a concrete use context.
03

Result

Benchmark output

Benchmark interpretation
If the case only asks for a product description, the compatibility rubric should not judge it. If the answer claims the product will work with the user's equipment, the rule is in scope.

Source confidence

Code-backed: Policy and Rubric types and their detail routes expose applicability fields and the links among governed standards, Cases, and evaluation checks. This page describes those product relationships; it does not define a portable rule language.

Related task pages

Reference / Correctness GovernancePolicies and RubricsUnderstand the governed relationship between behavior policies, applicability, binary rubrics, linked cases, and expert provenance.Troubleshooting / Recovery LibraryWeak Applicability LogicFix standards that are applied to the wrong cases or skipped where they matter.Task / Governance and ReproducibilityResolve conflicting correctness evidenceReconcile disagreement without hiding the Cases, expert judgments, sources, or versions that produced it.Quickstart / Learning ManualProduct quickstartConfigure one project foundation, one benchmark slice, one expert contribution, one evaluation, and one evidence-backed improvement.Concept / Operating ManualTask indexRoute correctness work to the current project foundation, benchmark workspace, evaluation, or improvement surface.

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Related docs

Correctness Governance Policies and Rubrics Understand the governed relationship between behavior policies, applicability, binary rubrics, linked cases, and expert provenance. Object Model Policies Define policies as reusable statements of what correct AI behavior requires. Object Model Rubrics Turn policies into binary, reviewable checks that explain pass and fail evidence.
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