Spot the directive-design flaw in this customer-support system prompt that's producing inconsistent behavior despite seemingly-clear instructions.

The flaw is that every rule in the system prompt is a prohibition. DO NOT, NEVER, AVOID, DO NOT, DO NOT, NEVER. Six in a row. A prohibition tells the model what not to do but does not tell it what to do instead. To follow each rule, the model has to imagine the prohibited action and then suppress it. When you stack six prohibitions, the model has to suppress six things at once, and the suppression often fails inconsistently. You can see the failure in the example reply. The user asked a normal question about delivery, and the assistant answered by quoting the prohibition back: 'I cannot make specific promises about delivery times.' The model fell back on restating the rule because there was no substitute behavior attached to it. The fix is to rewrite every prohibition as a positive 'when X, do Y' rule. 'For delivery questions, share the tracking link and the estimated arrival from order details.' Now the model has an action to take, and the answer is helpful instead of evasive.

The system prompt is a stack of six negative directives, and the assistant's reply shows the failure mode directly. The user asked a legitimate delivery question; the model parroted the prohibition back instead of helping. This is the canonical negation-heavy prompt anti-pattern. The mechanism is that each prohibition requires the model to model the forbidden behavior and suppress it. Six stacked suppressions overload the attention pattern. Some prohibitions stay tight, others slip, and the model often defaults to restating prohibitions because that is the safest visible behavior consistent with the rule. The fix is structural. Replace every rule with a positive substitute that names a recognition condition and an action. For delivery questions, share the tracking link and the estimated arrival from order details. For feature requests, acknowledge them and direct the user to the public roadmap. For refund requests outside policy, route to a formal claim via the support portal. The rewritten prompt covers the same surface but gives the model a clear action for every trigger. Per-rule compliance typically lifts ten to thirty points, and the visible failure of restating the prohibition disappears because the model has somewhere else to go.