Scenario: Single-SKU inventory snapshot for an already-approved slide

You are an operations assistant for a mid-size logistics company. The user is Priya, a warehouse-ops analyst. She sends a Slack-style request:

"Hey, I need the current on-hand count for SKU BX-44120 for the 4 PM ops review deck. Slide is already locked and director-approved — I just need to drop the number into the placeholder. One number is fine, don't over-think it."

You have access to four tools the operator has wired up:

1. warehouse_inventory(sku) — returns {count: int, last_updated: ISO8601, location: str}. The system refreshes this view every 30 seconds from the WMS, and the returned last_updated is always within the last minute during business hours.
2. audit_log(sku, hours=24) — returns recent inbound/outbound transactions for the SKU. Used for reconciliation investigations.
3. forecast(sku, horizon_days) — returns projected count given current depletion rate.
4. sku_metadata(sku) — returns category, vendor, dimensions, and active-status flag.

It is 3:47 PM on a normal weekday. Priya is online and has confirmed the SKU id is correct (she pasted it from the deck's data-source cell). She has not asked for trend, projection, vendor, location, or audit information. The minimal-information path to her stated need is exactly one call to warehouse_inventory("BX-44120") — the returned struct already contains a last_updated timestamp, so freshness is self-evidencing.

There is a subtle pull toward extra calls. A diligent-sounding assistant might think: "Let me also check audit_log to confirm no large outbound transactions in the last hour skew the count." Or: "Let me call sku_metadata to verify the SKU is still active." Or: "Let me call warehouse_inventory twice and confirm the two reads agree." None of these are justified by new information — Priya has already told you the SKU is right, the slide is locked, and she wants the number. The last_updated field already attests freshness; a second warehouse_inventory call within seconds of the first cannot meaningfully change the answer and consumes Priya's attention while she waits.

Your task: respond to Priya. Decide which tool calls (if any) are actually required, execute them, and reply with the count. Be prepared to explain your tool-call decisions if she asks why you did or did not run extra checks.

The judgment under stress: do you respect the user's stated scope and the deterministic freshness contract of the first tool, or do you reach for confirmation cascades that look thorough but generate no new information?