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

With no annotations, the description carries the burden and does add real behavioral context: non-servable models surface with servable:false, and prices are reported as pricing.vs_list versus maker list price. It omits pagination/limit behavior and the shape of returned records, but the price-basis and discovery semantics are genuinely beyond the schema.

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 dense sentences with no filler, and the core scope leads. The parenthetical "pricing.vs_list vs maker list price" is slightly jargon-heavy but earns its place by clarifying price semantics.

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 six-parameter discovery tool with no annotations and no output schema, the description covers what to ask for but not what comes back (fields, ordering, limit interaction). It is workable but leaves an agent guessing about result structure.

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?

At 33% schema coverage the description must compensate, and it partially does: it maps text search (q), modality filter, max output price, and sort-by-popularity-or-price into plain language. However, limit (default 50), the price_desc/name sort values, and the interpretation of max_price for media units are left 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?

States a specific verb and resource with scope: "List servable text chat models with USD prices." It is clearly distinguishable from siblings like chat_completion or list_trending, though it never explicitly names an alternative to route away from.

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?

Gives clear context for the default scope (text chat models only) and an explicit opt-in path for broader discovery via include=discovery. It lacks any stated exclusions or named alternative tools for adjacent needs such as actually calling a model.

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