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

No annotations are provided, so the description carries the full burden. It adds context about requiring valid domains from list_domains and gives an example, but does not describe pagination, error behavior, or the exact return shape. For a simple read operation, this is adequate but not deeply transparent.

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 three concise sentences with an illustrative example, front-loaded with the primary action and no redundant filler. Every sentence earns its place.

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 simple two-parameter listing tool, the description covers purpose, usage context, prerequisite, and an example. It states the output is model names, which partially compensates for the absence of an output schema. Missing pagination details are already in the schema.

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 schema already provides 100% description coverage for both parameters, including the enum for domain and a default for limit. The description reinforces that domain must exactly match list_domains output but does not add additional semantics beyond what the schema already states.

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 uses a specific verb 'List' with a clear resource ('data model names') and scope ('within a specific SDM domain'), distinguishing it from siblings like search_data_models. It also provides concrete examples and clarifies that it browses all models in a sector.

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?

Explicitly states when to use ('when the user wants to browse all models in a sector') and instructs to call list_domains first to confirm valid domain names. It does not explicitly name alternatives or when-not-to-use, but the context is clear.

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