search_models

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

With no annotations provided, the description carries the burden of behavioral disclosure. It explicitly says 'Search and list,' which implies a read-only operation, and it details the return format (models with pricing, provider, tier). It does not discuss rate limits or auth, but for a search tool these are less critical. The description provides useful behavioral context beyond just the tool's name.

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 concise and well-structured with an 'Args:' section followed by 'Returns:' clearly labeling each parameter and the output. Every line adds value, and the information is front-loaded with the purpose statement. It is appropriately sized for the tool's complexity.

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 the tool's moderate complexity (4 optional parameters, no required fields, output schema indicated), the description is complete. It explains all parameters, returns, and the nature of the tool. No critical information is missing for an agent to correctly select and invoke the tool.

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?

The input schema has no parameter descriptions (0% coverage), but the description fully compensates by explaining each parameter: query (text search on model id/name), tier (filter with allowed values), limit (range, default), and sort (examples of sort keys). This adds substantial meaning beyond the bare 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?

The description clearly states the tool's function: 'Search and list AI inference models with current pricing.' It identifies both the action (search/list) and the resource (AI inference models), and distinguishes itself from sibling tools such as list_providers (which lists providers) and get_model (which fetches a specific model).

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?

The description implies usage through its parameters and return values but does not explicitly state when to prefer this tool over alternatives. It lacks phrases like 'use get_model for a single model' or 'use list_providers for providers.' The context is clear, but no exclusions or alternative recommendations are provided.

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