Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover the safety profile (readOnly, idempotent, closed-world), so the description only needs to add operational context. It does: a 90-day retention window, per-engine granularity, and that raw model answers are included — meaningful disclosure about what the response contains.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tight sentences: the first front-loads what the data is, the second states the invocation condition. No filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description carries the burden of describing the return and does so (time window, engine breakdown, model answers). It omits pagination/result-size behavior, but that is a minor gap for a single-question history lookup.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the single parameter is fully documented ("question text, or enough of it to match"). The description's "by name" phrasing hints at fuzzy matching but adds nothing the schema doesn't already say, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a precise resource and scope: 90-day, per-engine history for one tracked question, and explicitly says it includes model responses. That is enough to separate it from the list-oriented sibling my_questions, though it never names a sibling directly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

"Use this when the user asks about one specific question by name" gives a concrete trigger condition that routes the agent correctly. It stops short of stating when NOT to use it or naming my_questions as the alternative for browsing questions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.