list_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 that the tool lists models and returns a JSON string, implying read-only behavior, but does not explicitly state side effects, permissions, rate limits, or pagination behavior beyond parameter limits. This is minimal disclosure for a tool with zero annotation coverage.

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 well-structured with clear sections: purpose, args, and returns. Each sentence serves a purpose, and the device model explanation is useful context. It is appropriately sized for a list endpoint with four optional parameters.

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 has four optional parameters and an output schema, the description covers the key aspects: function, parameter meanings, and return type. However, it misses guidance on when to choose list_models over search_models, which is a notable gap for a filtered-vs-unfiltered pair. Pagination defaults are in the schema, so not needed in prose.

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 description coverage is 0%, so the description must compensate. It does so effectively by listing all four parameters with meaningful descriptions: 'Filter by manufacturer ID', 'Filter by name (partial match)', 'Page number (starts at 1)', and 'Number of results per page (max 1000)'. This adds semantic value 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 verb and resource: 'List all models' and provides context that models are device models used in configurations. It distinguishes from search_models by emphasizing 'all models' rather than filtered search, though it does not explicitly name the sibling alternative.

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?

No guidance is given on when to use this tool versus alternatives like search_models or list_manufacturers. The description simply states the action without explaining conditions, exclusions, or scenarios where a different tool would be more appropriate.

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