Check Input

Narrow the ask before blaming the model.

Check Input helps you inspect the original ask and identify what it left missing, unclear, implied, conflicting, or unstated.

It is the first move in the Workbench: before assuming the model failed, inspect what structure the ask actually declared and what it forced the model to guess.

What It Does

Step 1: Copy the protocol below and run it with any AI system.

Step 2: Take the resulting Detected Gaps to the Gap Explorer.

Open Gap Explorer

What It Does Not Do

It does not diagnose the model.
It does not prove causality.
It does not classify a failure.
It does not produce receipts.
It does not replace DIVU.
It does not use Issues as Step 2 targets.

Copyable Protocol

Copy this artifact and paste it into an AI system with the input you want inspected.

AI Input Check Protocol

Review the following input for missing or ambiguous criteria that could force an AI system to guess.

Do not rewrite the input.
Do not solve the task.
Do not improve style.
Do not infer hidden intent.
Do not assume business context.
Do not assume authority.
Do not assume risk tolerance.
Do not assume the desired outcome beyond what the input states.

Only identify what is missing, unclear, ambiguous, conflicting, unstated, undefined, incomplete, or implied.

First, identify the following only if they are present in the input:
- actor
- trigger
- action
- outcome
- scope
- constraint
- dependency
- sequence

If an element is not present, write:
- [element]&#58; not specified

Then identify gaps using only this diagnostic vocabulary.

Elements:
- actor
- trigger
- action
- outcome
- scope
- constraint
- dependency
- sequence

Gap types:
- missing
- unclear
- ambiguous
- unstated
- undefined
- conflicting
- incomplete
- implied

Rules for findings:
- Express every finding as: [gap type] [element]
- Do not invent new labels
- Do not use synonyms
- Do not explain with long paragraphs
- Keep findings short and literal
- List only meaningful gaps that could change interpretation, behavior, or output
- If the input would require the AI system to guess, mark the relevant element as not specified or as a detected gap

Return results in exactly this format:

Input Summary
- actor: ...
- trigger: ...
- action: ...
- outcome: ...
- scope: ...
- constraint: ...
- dependency: ...
- sequence: ...

Detected Gaps
- ...
- ...
- ...

Now review this input:

[PASTE INPUT HERE]

Controlled Vocabulary

Elements

actor
trigger
action
outcome
scope
constraint
dependency
sequence

Gap Types

missing
unclear
ambiguous
unstated
undefined
conflicting
incomplete
implied

Every finding should use this shape: [gap type] [element].

Examples: missing actor, unclear scope, unstated constraint, conflicting dependency.

Example Output

Input Summary
- actor: not specified
- trigger: not specified
- action: write a refund email
- outcome: not specified
- scope: unclear
- constraint: not specified
- dependency: refund policy not specified
- sequence: not specified

Detected Gaps
- missing actor
- unstated outcome
- unclear scope
- unstated constraint
- missing dependency

Boundary

Check Input surfaces controlled gap terms. The Gap Explorer uses those terms to surface related Patterns and useful Lenses. These are related structural references, not a final diagnosis.

The Workbench helps find the structure. DIVU and related control systems can use declared structure to observe, control, and report what AI systems actually do.