get_mart_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. It describes the tool's behavior as retrieving name and description for all mart models, which is straightforward for a read operation. However, it lacks details on potential limitations like pagination, rate limits, or authentication requirements, leaving gaps in behavioral disclosure.

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 efficiently structured in two sentences: the first states the tool's action and output, and the second provides essential context about mart models. Every sentence adds value without redundancy, making it front-loaded and appropriately sized for the tool's simplicity.

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's low complexity (0 parameters, no output schema, no annotations), the description is largely complete. It explains what the tool does and the context of mart models. However, without annotations or output schema, it could benefit from mentioning the return format (e.g., list of objects) to fully compensate for the lack of structured data.

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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately does not discuss parameters, focusing instead on the tool's purpose and context, which aligns with the baseline expectation for tools without parameters.

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 specific action ('Get'), resource ('mart models'), and scope ('all mart models in the environment'). It distinguishes mart models from other dbt project components by explaining they are part of the presentation layer for end-user consumption, differentiating from sibling tools like get_all_models or get_dimensions.

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 provides clear context about when to use this tool by defining what mart models are and their purpose in the dbt project. However, it does not explicitly mention when not to use it or name specific alternatives among the sibling tools, such as get_all_models for broader scope or get_model_details for deeper information.

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