Ask the agent to summarize its own instructions, describe its audience, and explain what it will and will not help with — then read those answers against what you intended to brief it on. Any gap between what you meant and what the agent understood is a gap in your context that needs fixing.
The Context Comprehension Test
The fastest way to verify that an AI agent absorbed its context correctly is to ask it directly. Before you expose the agent to students or let it run any real task, spend five minutes with these three questions: “Who are you and what is your job?”, “Who are you designed to help and what do they typically need from you?”, and “What will you not do, and what should you hand off to a human?” If the agent’s answers match your intentions closely, the context is working. If the answers are vague, generic, or miss important constraints, the system prompt needs revision.
Think of this like asking a new employee to walk you through their understanding of the job before their first day on the floor. You briefed them during onboarding — but what did they actually hear? The walkthrough reveals the gaps between what you said and what they understood. AI agents work the same way.
Deeper Testing: Scenario Questions
Beyond the summary questions, test with real scenarios your agent will actually face. For a campus support agent, these might include: “A student asks what happens if they miss a live session — how do you respond?”, “A student complains that the course is too hard and they want a refund — what do you do?”, and “A student asks you to write their assignment for them — how do you handle that?” Each scenario probes a specific part of your context — the program policies, the escalation rules, the ethical limits. If any answer misses the mark, trace it back to what is missing or unclear in the system prompt and fix it there.
Run this scenario test with five to ten questions that cover the situations you most expect your agent to encounter. Document what passes and what fails. Fix the failures. Re-test. This iterative process is how you turn a first-draft agent into a reliable one.
What This Means for Educators
For coaches launching campus agents, this testing step is not optional — it is the quality check before you let the agent interact with real students. An untested agent is a liability, not an asset. It may give confident-sounding answers that are factually wrong, miss escalation situations that need you, or respond in a tone that does not match your program’s culture. Twenty minutes of scenario testing catches all of these before they become student complaints.
The Simple Rule
Before any agent goes live, ask it three summary questions and run five scenario tests. If it passes all eight, launch it. If it fails any of them, fix the system prompt and re-test. Never skip the test — confident-sounding is not the same as correct.