list_models

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

The readOnlyHint annotation already communicates that this is a safe read operation. The description adds that the result covers all models and includes specific fields, which is useful context, but there are no additional behavioral details such as pagination or ordering.

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, well-structured sentence with no filler. The operation and scope are front-loaded, and every remaining detail (kind, columns, owner, description) 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 parameterless list operation with a readOnly annotation and an output schema, the description is complete enough. It names the resource, scope, and visible attributes; nothing else is needed for an agent to select and invoke this tool correctly.

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 tool takes zero parameters and the schema coverage is trivially 100%, so there are no parameter semantics to clarify. The description appropriately focuses on what the tool returns rather than inputs.

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 operation ('List every model'), the resource ('the SQLMesh project'), and the returned attributes (kind, columns, owner, description). This distinguishes it from siblings like get_model, which targets a single model, and list_environments, which lists a different resource.

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?

There is no explicit statement of when to use this tool versus alternatives. The phrase 'every model' implies a broad overview use case compared to get_model, but the description does not directly say 'use this when you need all models' or name alternatives.

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