You want the desk using deep research aggressively — that's the point of paying for it. You also want the month's budget to survive contact with an enthusiastic analyst and an agent that happily runs forty deep queries before lunch. Those two wants collide in every team that gives AI tooling real spending power: usage you can't see until the invoice is usage you can't manage.

The naive fixes are both bad: rationing kills the aggressive usage you wanted, and trust-plus-hope kills the budget. The grown-up fix is the one every other metered resource gets — a guard in the loop: check the meter before the expensive step, degrade when it's thin, and make consumption visible while it happens instead of at month-end.

get_credit_status is the meter, free to read: wallet balance, plan tier, and today's remaining free quota, callable by any agent or analyst at any moment. That one tool turns budget from a month-end surprise into a loop variable.

deep_query is the spend it guards. The pattern is simple to state in an agent's instructions: before each research run, check credit status; below the floor, ask before proceeding or fall back to lighter tools. Analysts get self-serve visibility ("what's left today?" is a prompt, not a Slack thread to you), scheduled research jobs get spend-aware behavior instead of blind loops, and the desk's ambition stays high because the guardrail — not anxiety — is what's managing the budget.