list-ml-models

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

With no annotations, the description must disclose behaviors. It mentions pagination and service filtering but does not reveal key behaviors like response format, handling of deleted models (despite an 'include' parameter) or default behavior. The description is too minimal.

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, front-loaded sentence with no filler. Every word serves a purpose, making it highly concise and efficient.

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 and 7 parameters, the description lacks completeness. It does not explain what the tool returns, how pagination works (cursor-based via before/after), or default behaviors like omitting deleted models. A more detailed description is needed.

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 coverage is 100%, so baseline is 3. The description adds marginal value by summarizing pagination and service filtering, which are already clear from parameter names and schema descriptions. It does not elaborate on other parameters like 'fields' or 'extractFields'.

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 states 'List ML models with pagination and service filtering', clearly identifying the action and resource. It is specific and differentiates from other list-* tools by resource type, though not explicitly.

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 when to use (to list models with pagination and filtering) but does not provide explicit alternatives or when-not-to-use guidance. Siblings like get-ml-model-by-name or search-metadata are not mentioned.

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