Problem
When an assistant declines a request, people need to know whether it lacks access, lacks information, or cannot fulfill the request under the product’s rules.
Solution
State the limit plainly and explain what the person can do next. For missing access or an unsupported task, name the capability that is unavailable. For missing knowledge, say what information is needed or offer a search if available.
When a product rule prevents an answer, give a brief explanation without lecturing. Complete the parts of the request that can be handled, and make any omissions clear.
Offer a way to report a refusal that seems mistaken. Keep alternatives relevant to the original request.
Use when
The assistant cannot fulfill a request because of a capability, knowledge, or policy limit.
Don’t use when
The request is answerable with a caveat. Reaching for a refusal where a hedged answer would serve is the habit that trains people to take their work somewhere with fewer rules.
Trade-offs
A brief message may leave questions unanswered, while a long explanation can feel patronizing. Alternatives can help but may not meet the original need. Refusal messages need to stay consistent with the product’s actual capabilities and rules.
Checklist
- Can the viewer tell whether this is a capability, policy, or knowledge limit?
- Is there an offer of the nearest thing the assistant can do?
- How long is the message, and does it moralise?
- Is partial compliance possible instead of a full decline?
- Is there a way to report a wrong refusal, and does a human see it?
- Is the false-positive rate measured at all?
- Does the refusal contradict what the first-run state or the prompt starters promised?
- Does it read the same way on the tenth occurrence as the first?
- Is a policy decline visually distinguishable from an error?
- Can the viewer tell whether rephrasing would help?
Compare
Claude tends toward explaining the boundary and offering an adjacent version of the request. The turn stays productive, and it runs long. ChatGPT favours shorter declines with a suggested reframing, so the next move is usually visible in the message itself. Gemini more often redirects to search for knowledge-limited cases, converting a decline into a handoff rather than an ending. Microsoft Copilot in an enterprise tenant has a fourth case the consumer products lack, where the refusal is about the viewer’s permissions rather than the model’s policy, and saying which one it is matters more there than anywhere else.
Related
Generation error indicates a technical failure. Knowledge cutoff notice flags potentially outdated information. First-run state explains limits before people begin.
Prompt starters set expectations about supported requests. Usage meter handles limits on how much the assistant can be used.