metadata
language:
- en
- id
license: mit
tags:
- humanoid
- instruction-intent
- pre-execution
- safety
- reasoning
- llm
instruction-intent-filter
Model Description
instruction-intent-filter is a language model designed to analyze the intent behind natural language instructions before execution.
The model evaluates whether an instruction’s intent is clear, valid, contradictory, incomplete, or unsafe. It is intended to be used as a filtering layer for humanoid and agent systems prior to task planning or execution.
Intended Use
- Instruction intent filtering
- Pre-execution decision making
- Humanoid and agent safety layers
- Human–AI interaction control
Output Format
The model outputs JSON only with the following structure:
{
"label": "VALID | AMBIGUOUS | CONTRADICTORY | INCOMPLETE | UNSAFE",
"confidence": 0.0
}