list_evaluations

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

No annotations are present, so the description carries the behavioral burden. 'List' implies a read-only operation, but the description does not explicitly confirm no side effects, ordering, pagination, or return details. It is minimally transparent but leaves key behavioral traits unstated.

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 entire description is a single front-loaded sentence with no redundant words. It conveys the action, object, and scope efficiently.

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 one-parameter list tool with no output schema or annotations, the description covers the core purpose but omits return structure, filtering behavior, and relationship to named siblings. It is adequate but has gaps an agent would need to resolve from context or by invoking the tool.

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%, and the description's 'for a project' adds semantic context that project_name is the project being queried. However, this mostly restates the parameter's name and does not explain accepted formats, required identifier types, or defaults.

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 uses a specific verb ('List') with a clear resource ('evaluation runs and their scores') and scope ('for a project'). This distinguishes it from siblings like get_evaluation_summary, which implies a single summary object, and list_datasets, which targets 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?

The phrase 'for a project' gives contextual usage, but there is no explicit guidance on when to choose this tool over get_evaluation_summary or list_projects. Usage is implied rather than stated with alternatives or exclusions.

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