LEN-0210
Invariant Lens
Verifies that declared invariants are structurally enforceable and not contradicted by observed structure.
Primary Pattern Matches
Invariant Breakage
A structural condition where an observed state violates a declared invariant that is supposed to remain true.
Lens Application
The Invariant Lens is a primary inspection mechanism for Invariant Breakage because it compares declared invariants with the structural conditions that are supposed to preserve them. It helps surface places where enforcement is missing, inconsistent, or contradicted by observed states without treating the finding as a final verdict.
Inspect For
- Declared invariants contradicted by observed state
- Missing structural enforcement of invariant conditions
- Exceptions or transitions that bypass invariant protection
- Conflicting rules that make the invariant unstable
Avoid
Treat a contradiction as an inspection signal rather than conclusive evidence without checking whether scope, timing, or enforcement boundaries affect the observation.
Schema Breakage
A structural condition where an instance, graph, payload, or object violates the type, shape, or rule requirements of a declared schema.
Lens Application
The Invariant Lens is a primary inspection mechanism for Schema Breakage because it compares declared schema invariants with the actual structure being observed. It helps surface places where required fields, types, cardinalities, relationships, or validation rules are structurally contradicted or cannot be consistently enforced.
Inspect For
- Required fields or nodes that are missing
- Type, shape, or cardinality mismatches
- Constraints contradicted by observed structure
- Invariants that validation cannot reliably enforce
Avoid
Treat structural mismatches as inspection signals rather than confirmation that Schema Breakage has been established.
Threshold Breach
A structural condition where an observed metric, value, state, or condition exceeds a declared quantitative or qualitative threshold.
Lens Application
The Invariant Lens is a primary inspection mechanism for Threshold Breach because it examines whether the threshold functions as a true invariant or only an informal expectation. It helps surface mismatches between declared constraints and observed states that exceed, bypass, weaken, or contradict those constraints.
Inspect For
- Declared limits, ranges, or forbidden states
- Observed values or conditions beyond those limits
- Enforcement gaps or bypass paths
- Conflicts between invariant claims and system behavior
Avoid
Treat an exceeded value as an inspection signal rather than confirmation that Threshold Breach has occurred without checking whether the threshold was structurally declared, enforceable, and relevant to the observed condition.
Secondary Pattern Matches
Authority Collision
A structural condition where multiple authorities claim governance over the same region without a declared precedence or resolution rule.
Lens Application
The Invariant Lens applies indirectly to Authority Collision by examining whether required governance invariants still hold when multiple authorities govern the same region. It can surface stress points where enforcement assumptions, precedence expectations, or consistency requirements are undermined by unresolved authority overlap.
Inspect For
- Invariants depending on a single governing authority
- Conflicting rules applied to the same governed region
- Missing precedence or escalation conditions
- Enforcement paths blocked by overlapping authority claims
Avoid
Treat invariant tension as a supporting inspection signal, not confirmation that Authority Collision exists.
Related Issues
Action Triggered by Confidence Score
A confidence score, certainty label, risk level, or probability-like value triggers an action without enough approval, calibration, or authority control.
Agent Gets Conflicting Tool Authority
An agent receives conflicting authority signals about whether, when, or how it may use a tool, connector, function, or integration.
AI Output Breaks Parser
The AI output causes a parser, validator, importer, or structured-output consumer to fail.
Approval Depends on Output That Needs Approval
A required approval depends on an AI output or workflow result that itself cannot be produced or trusted until approval is granted.
Conflicting Instructions From Different Authorities
Instructions from different sources, roles, policies, prompts, tools, or workflow authorities conflict without a clear rule for which one governs.
Downstream Steps Magnify Hallucinated Claim
A hallucinated or unsupported claim from an AI output is reused by later workflow steps until it becomes more influential than the evidence supports.
Duplicate Fields With Same Meaning
The AI returns multiple fields, labels, sections, or structured elements that carry the same meaning and create ambiguity about which one should be used.
Duplicate Output Sections
The AI repeats sections, headings, blocks, or output areas in a way that creates redundancy, confusion, or downstream handling problems.
Format Rule Too Weak
The format instruction is too vague, incomplete, or optional to reliably produce output that satisfies the expected structure.
Hallucinated Fields
The AI adds fields, keys, attributes, columns, or structured elements that were not declared, requested, or allowed by the expected schema.
Hidden Rule Overrides Visible Instruction
A hidden, upstream, system, policy, tool, or product rule changes or overrides the visible instruction the user expects the AI to follow.
Human Review and Automation Disagree
A human review result and an automated AI or workflow result disagree without a declared rule for resolving the difference.
Invalid JSON Output
The AI returns malformed JSON or structured output that cannot be parsed.
Missing Required Fields
The AI returns structured output that omits fields required by the schema, workflow, parser, form, or downstream consumer.
Nested Fields Do Not Match
The AI returns nested structured fields whose internal shape, hierarchy, parent-child relationship, or contained values do not match the expected structure.
Output Breaks the Next Step
The AI output looks acceptable by itself but cannot be used by the next tool, workflow step, parser, reviewer, or downstream consumer.
Output Exceeds Length Limit
The AI output exceeds a declared length, token, word, character, section, field, or size limit.
Parallel Reviews Never Agree
Parallel AI, human, workflow, or tool reviews keep producing different results without resolving into a shared decision state.
Permissions Conflict After Being Combined
Permissions, approvals, roles, policies, or authority rules that seem valid separately conflict when combined in the same workflow or AI action.
Policy Decision Depends on Itself
A policy decision requires the outcome of the same policy decision before it can be made.
Risk Score Triggers Wrong Escalation
A risk score, severity label, confidence value, or threshold result triggers the wrong escalation path.
Risk Signal Escalates Beyond Evidence
A risk signal, warning, score, or concern escalates farther than the available evidence supports.
Same Case Has Conflicting Policies
The same case appears to be governed by multiple policies, rules, or standards that point to incompatible outcomes.
Schema Reference Loops Without Base Case
A schema, field, type, object, or structured reference points through a loop without a base case that allows validation or interpretation to resolve.
Severity Increases Without New Evidence
The severity, risk, confidence, or escalation level increases even though no new evidence has been added.
Single Field Carries Too Many Obligations
One field, label, score, status, or structured value is expected to carry too many meanings, decisions, or workflow obligations.
Small Issue Keeps Escalating
A small issue, warning, uncertainty, or correction keeps increasing in severity, scope, or workflow impact across later steps.
Tool Call Contract Mismatch
The AI or agent calls a tool with names, arguments, types, modes, or shapes that do not match the declared tool interface.
Tool Rules and Prompt Rules Conflict
Tool, connector, function, or MCP rules conflict with prompt instructions, causing the AI or agent to face incompatible requirements.
Validation Result Changes on Retry
A validation, grading, review, classification, or pass/fail result changes after retry even though the input and declared validation rules did not change.
Wrong Field Types
The AI returns fields with values whose types do not match the expected schema, such as strings where numbers, booleans, arrays, objects, or enums are required.