Spread & Escalation
Problems where small errors, local exceptions, risk signals, retries, permissions, or outputs spread downstream, grow in consequence, or trigger broader actions.
Primary Issues
- 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.
- 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.
- Repair Step Created New Breakage
A repair, correction, retry, or fix step addresses one problem but introduces a new failure elsewhere.
- Policy Exception Spreads Too Far
A narrow policy exception, allowance, or special case spreads beyond its intended scope and begins governing broader cases.
- Risk Score Triggers Wrong Escalation
A risk score, severity label, confidence value, or threshold result triggers the wrong escalation path.
- Small Error Spreads Into Large Failure
A small AI, output, routing, or workflow error propagates through later steps until it becomes a larger failure.
- Early Model Output Gets Overweighted Downstream
An early AI output receives too much authority in later workflow steps, decisions, reviews, or generated artifacts.
- Risk Signal Escalates Beyond Evidence
A risk signal, warning, score, or concern escalates farther than the available evidence supports.
- Local Rule Spreads to Broader Cases
A rule intended for one local case, file, context, user, workflow, or exception begins affecting broader cases.
- 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.
- Small Issue Keeps Escalating
A small issue, warning, uncertainty, or correction keeps increasing in severity, scope, or workflow impact across later steps.
- Agent Permission Expands Over Steps
An agent begins with limited permission but gains, assumes, or exercises broader authority as the workflow continues.
- Review Escalates Without Stop Condition
A review process keeps escalating, re-reviewing, or adding scrutiny without a declared condition for stopping.
- Local Exception Grows Into Policy
A local exception, special case, or one-off allowance begins to function like a general policy.
- Severity Increases Without New Evidence
The severity, risk, confidence, or escalation level increases even though no new evidence has been added.
- Small Change Produces Large Downstream Effects
A small prompt, schema, policy, output, or workflow change creates unexpectedly large effects in downstream steps.
Also Related Issues
- Model Output Triggers Unapproved Action
AI output causes, recommends, or triggers an action that has not passed the required approval, permission, or authority check.
- 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.
- 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.
Ontology Metadata
- Code
CAT-0110- Version
[email protected]- Ontology release
- 0.1.0
- Updated
- 2026-05-10T00:00:00Z
History
No public history entries recorded.