PAT-0170 - Constraints Underspecified
A structural condition where declared constraints are insufficient to eliminate ambiguity or multiple admissible states.
Primary Lenses
- LEN-0160 - Constraint Sufficiency Lens
Evaluates whether declared constraints are sufficient to eliminate structural degrees of freedom.
Secondary Lenses
- LEN-0180 - Determinism Lens
Evaluates whether identical structural inputs produce equivalent structural outputs across repeated executions.
- LEN-0290 - Variance / Entropy Lens
Measures structural variability across repeated or comparable evaluations and identifies divergence beyond expected bounds.
Primary Issue Matches
- Format Rule Too Weak
The format instruction is too vague, incomplete, or optional to reliably produce output that satisfies the expected structure.
- 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.
Supporting Issue Matches
- 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.
- Diagnostic Area Has No Coverage
A known diagnostic area, failure mode, requirement, or review dimension has no Issue, check, rubric item, or workflow coverage.
- Evaluation Rubric Has Coverage Gap
An evaluation rubric, grading standard, or review checklist leaves part of the required evaluation space uncovered.
- Invalid JSON Output
The AI returns malformed JSON or structured output that cannot be parsed.
- 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.
- 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 Exceeds Length Limit
The AI output exceeds a declared length, token, word, character, section, field, or size limit.
- 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.
- 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.
- Review Rubric Missing Required Criteria
A review rubric, grading rule, evaluation checklist, or classification standard lacks criteria required to make the review reliable.
- Same Instructions Allow Different Outputs
The same instructions are broad or underspecified enough to allow materially different outputs that all appear compliant.
- 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.
- 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.
- Workflow Step Lacks Required Conditions
A workflow step can run, route, approve, reject, or continue without the required conditions being declared or checked.
Ontology Metadata
- Code
PAT-0170- 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 Pattern ontology entry: Constraints Underspecified.
Receipt impact: None