vunet_list_data_models

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the purpose and category filtering, with no mention of pagination, rate limits, or whether the list is exhaustive. This is insufficient for a list operation with no other context.

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 sentence that front-loads the main action. It is efficient, though the word 'common' could be more precise. Slightly more context would improve it without sacrificing conciseness.

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 list tool with one parameter and no output schema, the description is minimally adequate. It fails to mention the response format (e.g., list of model names with descriptions) or that it returns only common models. Given no annotations, more context would be beneficial.

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 the schema already documents the category parameter. The description adds little beyond restating the categories and the concept of organization. Baseline of 3 is appropriate as no additional semantic value is provided.

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 specifies the verb 'List' and the resource 'common Vunet data models', and indicates organization by category. This distinguishes it from the sibling tool vunet_fetch_datamodels, which likely retrieves details of specific models.

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?

Usage is implied but not explicit. The description does not state when to use this over alternatives, nor does it provide exclusions. Sibling names give some context, but no direct guidance.

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