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

No annotations are provided, so the description carries the burden — and it does disclose cost ('Free'), data provenance ('source: models.dev, provider-declared prices', flagging that prices are provider-declared rather than authoritative), and result ordering ('cheapest effective cost first'). It omits whether prices are cached/stale, what happens when filters match nothing, and any rate/auth behavior.

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?

Four dense sentences, front-loaded with the one-word cost signal and the output shape, then filters, then ordering, then the call-to-action. No filler and nothing buried.

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 13 optional params, no annotations and no output schema, the description compensates by naming the returned fields (pricing, context window, capabilities) and the sort order. Remaining gaps are the default/max result count and limit behavior, which the schema only bounds (1-50) without a stated default.

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 69% schema coverage the description adds value only partially: it enumerates the cost/context/provider/capability filters (mostly restating schema descriptions) and usefully covers needs_tools and needs_reasoning, which have no schema description. It leaves limit, paid, workload_output_tokens, and the exact workload-based ranking semantics unexplained, and 'cheapest effective cost first' doesn't clarify how workload_input_tokens/workload_output_tokens change ranking.

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 + resource: ranked (model, provider) pairs enriched with per-1M-token pricing, context window and capabilities. The 'ranked ... cheapest first' framing implicitly separates it from the plain lookup sibling get_model, but it never names that sibling, so the differentiation is inferential rather than stated.

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 an explicit trigger: 'Call this before routing inference so you buy the right model at the right price,' which tells the agent the workflow stage. It does not name an alternative tool or state when not to use it (e.g., when you already know the exact model and should call get_model).

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