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

Given annotations already mark it read-only and idempotent, the description adds substantial behavioral context: natural-language interpretation, echoed interpreted_filters, explicit-param precedence, published/playable freshness constraints, listing-only behavior, content-rating default, and zero-result relaxation behavior. This is exactly the kind of operational detail an agent needs beyond the safety annotations.

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 description is dense but front-loaded with the core action, then layers query interpretation, special title behavior, return constraints, zero-result handling, and output requirements. Every clause contributes useful selection or invocation guidance for a complex 14-parameter search tool.

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?

For a complex search tool with an output schema and read-only annotations, the description covers the critical gaps: interpretation behavior, filter precedence, freshness constraints, zero-result semantics, relaxation usage, and attribution requirements. An agent has enough information to select and call it correctly.

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 low at 21%, so the description has to compensate for many of the 14 parameters. It meaningfully explains the main filter families, natural-language phrase handling, explicit-param precedence, include_listing_only, plays behavior, and content_rating_max default, though it leaves some parameters such as limit, min_quality, and exclude_genres largely to the schema.

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?

States a specific verb and resource: find web games from a natural-language query plus optional filters. It also distinguishes special behavior for titles via games_like results, so the agent can tell this is the primary search tool rather than a detail or random-selection 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?

Clearly implies use when searching by natural-language query or filters, and explicitly explains how 'like {title}' routes to games_like results. It also says explicit params win over interpreted phrases, but it does not explicitly contrast with siblings such as trending, random_game, or get_game.

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