LEN-0290 - Variance / Entropy Lens

Primary Pattern Matches

• PAT-0110 - Asymmetric Structure

  A structural condition where comparable regions receive unequal rule, constraint, or authority application without a declared differentiation rule.

• PAT-0270 - Density Spike

  A structural condition where nodes, edges, dependencies, decisions, or effects concentrate sharply within a localized region beyond declared thresholds.

• PAT-0290 - Divergent Outputs

  A structural condition where parallel evaluations under comparable scope and shared authority produce non-equivalent outputs.

• PAT-0300 - Escalation Growth

  A structural condition where impact, authority, scope, or consequence increases across sequential states without a declared limiting mechanism.

• PAT-0210 - Non-Deterministic Execution

  A structural condition where equivalent inputs and declared constraints produce divergent outputs across executions.

Secondary Pattern Matches

• PAT-0170 - Constraints Underspecified

  A structural condition where declared constraints are insufficient to eliminate ambiguity or multiple admissible states.

• PAT-0320 - Convergence Failure

  A structural condition where sequential or parallel states fail to resolve into an equivalent or coherent structure under shared authority and constraints.

• PAT-0360 - Propagation Amplification

  A structural condition where an effect, declaration, authority, constraint, or state increases in scope or intensity as it propagates beyond declared bounds.

• PAT-0410 - Unconstrained Expansion

  A structural condition where a region, process, authority, or effect expands without governing constraints limiting growth.

Related Issues

• Action Changed Something Else Too

  An AI or agent action makes the requested change but also changes another object, field, file, state, rule, or workflow element that was not supposed to change.

• 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 Keeps Expanding the Task

  The agent repeatedly expands the task, plan, scope, or next-step list instead of completing the declared work.

• Agent Never Settles on Final Answer

  The agent keeps revising, rechecking, planning, or branching instead of converging on a final answer or completed result.

• Agent Permission Expands Over Steps

  An agent begins with limited permission but gains, assumes, or exercises broader authority as the workflow continues.

• AI Forgets Earlier Constraints

  A constraint, instruction, preference, or decision that should persist through the task stops affecting later output.

• Answer Has Too Many Paths

  The answer presents too many possible paths, interpretations, options, or next steps without enough structure to choose among them.

• Context Leaks Between Tasks

  Context, assumptions, constraints, examples, files, or decisions from one task affect another task where they should not apply.

• Diagnostic Area Has No Coverage

  A known diagnostic area, failure mode, requirement, or review dimension has no Issue, check, rubric item, or workflow coverage.

• 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.

• Early Model Output Gets Overweighted Downstream

  An early AI output receives too much authority in later workflow steps, decisions, reviews, or generated artifacts.

• Evaluation Rubric Has Coverage Gap

  An evaluation rubric, grading standard, or review checklist leaves part of the required evaluation space uncovered.

• Format Rule Too Weak

  The format instruction is too vague, incomplete, or optional to reliably produce output that satisfies the expected structure.

• 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.

• Local Exception Grows Into Policy

  A local exception, special case, or one-off allowance begins to function like a general policy.

• Local Rule Spreads to Broader Cases

  A rule intended for one local case, file, context, user, workflow, or exception begins affecting broader cases.

• Merge Step Leaves Unresolved Differences

  A merge, reconciliation, or consolidation step combines outputs or reviews but leaves important differences unresolved.

• Missing Fallback for Unavailable Information

  The task does not declare what the AI should do when required information, sources, tools, fields, or evidence are unavailable.

• Model Output Triggers Unapproved Action

  AI output causes, recommends, or triggers an action that has not passed the required approval, permission, or authority check.

• Multiple Policies Say the Same Thing

  Multiple policies, rules, or guidance documents express the same requirement, creating redundancy and uncertainty about which one governs.

• One Prompt Carries Too Many Meanings

  A single prompt carries too many meanings, goals, roles, constraints, or implied tasks for the AI to interpret consistently.

• Output Breaks After Model Change

  Output that previously worked begins failing after a model, mode, runtime, or product behavior changes.

• 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.

• Policy Exception Spreads Too Far

  A narrow policy exception, allowance, or special case spreads beyond its intended scope and begins governing broader cases.

• Prompt Behavior Changed Without Version Change

  A prompt begins producing different behavior even though no prompt version, model version, workflow version, or declared dependency change is recorded.

• Prompt Does Not Say What to Exclude

  The prompt declares what to include but does not declare what should be excluded, allowing unwanted scope, sources, content, or actions into the result.

• Prompt Has Too Many Valid Interpretations

  The prompt allows too many reasonable interpretations, causing the AI to choose among valid paths without enough guidance.

• Prompt Only Works After Retry

  The prompt fails, misroutes, or produces an unusable response on one attempt but works after retry without a meaningful change to the input.

• Repair Step Created New Breakage

  A repair, correction, retry, or fix step addresses one problem but introduces a new failure elsewhere.

• Repeated Constraints Create Confusion

  Repeated constraints, instructions, limits, or exclusions make the task harder to interpret instead of clearer.

• Results Vary Too Much

  Repeated or comparable runs produce outputs that vary more than the task, workflow, or user can tolerate.

• Retrieval Exceeds Evidence Limit

  The AI retrieves, uses, cites, or considers more evidence than the task permits or more than the review surface can support.

• Retry Makes the Problem Worse

  A retry, repair attempt, regeneration, or follow-up instruction increases the error, expands the failure, or creates additional breakage instead of narrowing the problem.

• Review Escalates Without Stop Condition

  A review process keeps escalating, re-reviewing, or adding scrutiny without a declared condition for stopping.

• Review Outcome Changes Unrelated Environment

  A review result, approval, rejection, or classification changes state outside the environment, case, file, or workflow it was meant to govern.

• Review Queue Becomes Bottleneck

  A review queue, approval path, or validation stage accumulates too much work and begins blocking the workflow.

• Review Rubric Missing Required Criteria

  A review rubric, grading rule, evaluation checklist, or classification standard lacks criteria required to make the review reliable.

• 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.

• Routing Path Cycles Back to Start

  A routing path sends the case back to the starting point or an earlier step without resolving the condition that caused the route.

• Same Instructions Allow Different Outputs

  The same instructions are broad or underspecified enough to allow materially different outputs that all appear compliant.

• Same Rule Declared in Multiple Places

  The same rule, constraint, instruction, or policy appears in multiple places, creating redundancy and possible drift.

• Same Workflow Check Happens Twice

  The same review, validation, approval, routing, or safety check occurs more than once in the workflow without a clear reason.

• Severity Increases Without New Evidence

  The severity, risk, confidence, or escalation level increases even though no new evidence has been added.

• Similar Cases Route to Different Outcomes

  Similar inputs, cases, prompts, or workflow states are routed to different outcomes without a declared difference that explains the split.

• 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.

• Single Step Carries Too Many Decisions

  One prompt, workflow step, review stage, or agent action carries too many decisions for the system or user to evaluate cleanly.

• Small Change Produces Large Downstream Effects

  A small prompt, schema, policy, output, or workflow change creates unexpectedly large effects in downstream steps.

• Small Error Spreads Into Large Failure

  A small AI, output, routing, or workflow error propagates through later steps until it becomes a larger failure.

• Small Issue Keeps Escalating

  A small issue, warning, uncertainty, or correction keeps increasing in severity, scope, or workflow impact across later steps.

• Task Has No Clear Limit

  The task does not declare where the AI should stop, what is out of scope, or what counts as enough work.

• Task Progress Is Lost Midway

  The AI loses track of completed work, prior decisions, current position, or remaining steps before the task is finished.

• Too Many Tool Calls

  The AI or agent makes more tool calls, searches, retrievals, API calls, or integration actions than the task requires or permits.

• Tool Exists but Required Inputs Are Missing

  A usable tool or integration exists, but the AI or agent does not have the required inputs, permissions, fields, identifiers, or context needed to call it correctly.

• 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.

• Workflow Loops Through Review Without Resolution

  A workflow repeatedly sends work through review, repair, or escalation without reaching an approved, rejected, or otherwise resolved state.

• Workflow Step Lacks Required Conditions

  A workflow step can run, route, approve, reject, or continue without the required conditions being declared or checked.

• Workflow Waits on Step That Waits Back

  A workflow step waits for another step that also waits on the first step, creating a blocking loop.

Ontology Metadata

Code

LEN-0290

Version

[email protected]

Ontology release

0.1.0

Updated

2026-05-10T00:00:00Z

History

• 0.1.0 — 2026-05-10T00:00:00Z — Created

  Promoted reviewed Lens ontology entry: Variance / Entropy Lens.

  Receipt impact: None

View full ontology changelog