Hallucination guardrails are instructions that reduce the chance a model will invent facts, overstate certainty, or hide missing evidence. They do not make hallucination impossible, but they make unsupported output easier to catch and less likely to slip through review.
Why it matters
As prompts become more structured and more confident, the risk is not only wrong content. It is wrong content that looks clean. Guardrails are one of the main tools for preventing that failure mode.
Example in practice
A research prompt might include guardrails such as:
- use only the provided material
- note when the evidence is incomplete
- distinguish observation from inference
- do not fabricate citations or examples
These rules are especially helpful when a prompt also uses Objective Execution Mode, because that mode can make the answer sound more certain.
What to look for
Good hallucination guardrails usually:
- limit the evidence source
- require uncertainty handling
- block invented specifics
- encourage clarification when inputs are missing
- make review easier
Common confusion
Hallucination guardrails are not the same as constraints in general. They are a specific class of constraint focused on truthfulness and evidence discipline. They also do not replace an Output Contract; a well-structured hallucination is still a hallucination.
Related context
Read Prompt Constraints for the broader category of limits and rules. For implementation patterns, continue with Review Objective Execution Prompts Before Sharing and Why Objective Execution Prompts Need Guardrails.