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

Beyond the annotations (read-only, open-world, etc.), the description discloses significant behavioral traits: server-side vs local filtering, cost structure (one request per list page plus one per shelf page), and output annotation. This adds valuable context that annotations do not provide.

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?

Every sentence earns its place: purpose, capability, rationale, cost, and alternative. It is front-loaded with the main action and includes no filler or repetition. Efficient and well-structured.

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?

Given no output schema, the description explains the return includes provenance annotations but not exact fields. It covers complexity (filtering behavior, cost, alternative) well for a search tool, though a bit more detail on response format would be ideal. Still highly complete.

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 only 33%, so the description should compensate by explaining parameter meanings. It offers only indirect hints (shelf/list halves, page costs) without detailing genre, max_games, include_lists, or release_platform. This leaves most parameter semantics unaddressed.

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 clearly states the tool finds games across shelves and custom lists simultaneously, with provenance annotation. It explicitly differentiates from query_library by noting the heavier cost and recommending query_library for shelf-only queries, making it highly distinguishable.

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?

Provides explicit when-to-use and when-not-to-use guidance. It explains that list pages lack filters, necessitating this tool for combined shelf+list searches, and directly advises using query_library when shelves suffice. This is model guidance.

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