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

With no annotations, the description carries the full behavioral burden. It discloses the returned fields and the slim-mode behavior, but it does not state read-only status, authorization requirements, pagination behavior, or what happens when the project has no mocks.

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 two tight sentences: the first states purpose and grouping, and the second states return contents plus the slim alternative. It is front-loaded with no wasted text.

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 that there is no output schema, the description usefully explains the returned fields and the slim return shape. The main gap is the lack of sibling differentiation from search_mocks, but the parameter schema is rich enough to cover filtering details.

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 100%, so the schema already documents all five parameters including path, label, method, and slim. The description repeats the slim behavior but does not add meaning beyond the schema, so the baseline of 3 is appropriate.

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 states a specific verb and resource: list all mock API endpoints in a project, organized by collections. That is clear enough to act on, but it does not distinguish this tool from the sibling search_mocks, which also appears to retrieve mocks.

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 guidance on when to use list_mocks versus alternatives such as search_mocks or get_mock_detail. The only usage-like cue is the slim parameter for token efficiency, which is a parameter behavior rather than when-to-use guidance.

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