models_list

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

No annotations are provided, so the description must fully disclose behavior. It only states a read operation ('List models') but omits side effects, authorization needs, rate limits, or whether pagination is supported. For a tool with no annotations, this is insufficient.

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 a single concise sentence that front-loads the action. Every word is functional with no redundancy.

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?

Despite one parameter and simple action, the description lacks details on return format, pagination, or filtering. Without an output schema, the agent is left guessing about the response structure, making it incomplete for a list operation.

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?

With 0% schema description coverage, the description adds meaning by explaining the 'project' parameter accepts IDs, slugs, or URIs. This compensates partially, though exact format constraints are missing, earning a score of 4.

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 lists models in a project and enumerates the accepted identifiers (project id, slug, username/slug, or URI). This active verb and resource combination distinguishes it from siblings like models_get and datasets_list.

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 specifies how to identify the project via the parameter, giving contextual guidance. However, it does not explicitly state when to use this tool over alternatives, nor does it mention when not to use it, leaving a slight gap.

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