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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the description's job is to add data semantics, which it does: dynamic columns are combined with the same publication's shared index exactly as the website does, and price/status columns are validated against the item index. That tells an agent the returned values are reconciled and publication-dependent rather than raw or estimated. It does not discuss size, pagination, or freshness, so it falls short of a 5.

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?

The core action and dataset enumeration are front-loaded, and the closing exclusions earn their place. The middle clause about index merging is dense and packs three ideas into one sentence, slightly reducing scannability, but nothing is redundant with the schema in the prose.

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?

An output schema exists, so return-field documentation is not required, and annotations cover the safety profile. The description covers the remaining decision-relevant facts: which dataset keys exist, which is the default, how dynamic values are derived, and what the tool deliberately does not provide.

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 description coverage is 100%, so the baseline is 3 and the description must add meaning to earn more. It does add semantic content beyond the schema by explaining what 'dynamic' means operationally (dynamic columns merged with the same publication's shared index) and by flagging which key is the website default, rather than merely restating the enum-like list.

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 opens with a specific verb and resource ('Get one published FC27 card-price dataset and return its native compact fields'), making the scope unambiguous. It also distinguishes itself from computed/historical siblings via the closing 'No computed estimates or history', though it stops short of naming the sibling tool an agent should use instead.

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?

It gives clear selection guidance for the one parameter: the four named publications are each labeled (Console standard, PC standard, Console dynamic, PC dynamic) and it states the omit-for-default behavior. It does not explicitly direct the agent elsewhere for derived or historical data, so the routing to alternatives is only implied by 'No computed estimates or history'.

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