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

Annotations already cover safety (readOnly, idempotent, non-destructive), and the description adds substantial extra context: best_image and its meaning, the url/remake url semantics, that remake editions are nested under the remake, and the newest_edition_year vs in_production distinction. This is rich behavioral/output disclosure beyond the structured fields.

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?

It is on the long side and the quoted example questions are slightly cluttered, but every sentence carries substantive information (edition grouping, best_image fields, ID formats, field semantics) and the return shape is front-loaded. Little is wasted, though it could be tightened.

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 return-value burden and does so thoroughly, explaining editions, pricing, images, and the year/production fields. An agent has everything needed to call it and interpret the result.

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%, so baseline is 3, but the description adds real value: concrete examples of slug (godzilla-2021), OPDB group ID (weeP), and OPDB machine ID (GweeP-MW95j) disambiguate the id formats, and it explains the include=credits effect beyond the schema's one-line boolean description.

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 names a specific resource (pinball machine details) and enumerates exactly what it returns: pricing, production status, editions (Pro/Premium/LE), images, tags, description, and rules links. The example queries ('how much is the Godzilla Premium, and is it still made?') make the scope concrete and distinguish it from a generic search tool.

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 context for use via representative questions and lists the accepted identifier forms, and it points to `?include=credits` for design-team data (a soft alternative to get_game_credits). It doesn't explicitly state when not to use it or name sibling tools as alternatives, so it falls short of a full 5.

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