evaluate

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only says the tool returns data, but does not state whether evaluation has side effects, whether it requires a loaded model, what 'global evaluation' means, or what kind of expression syntax is expected.

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 sentence and front-loads the primary action. It is appropriately brief, though the parenthetical 'or global evaluation' introduces ambiguity without explanation, slightly reducing structural clarity.

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?

Although an output schema exists, the description remains incomplete for a two-parameter tool with no annotations. It fails to clarify the evaluatee, the dataset semantics, or how this tool fits into the broader API workflow alongside siblings. An agent would need to inspect schemas or guess to invoke it correctly in non-trivial contexts.

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 echoes the 'expression' concept for expr but adds no detail about the dataset parameter, expression syntax, or the relationship between 'global evaluation' and the inputs. This is minimal added meaning over the raw schema field names.

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 clear verb and resource: 'Evaluate an expression (or global evaluation) and return data.' It identifies the tool's core action and output. However, it does not differentiate it from sibling tools like exec_model_api, and the meaning of 'global evaluation' is left vague.

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 guidance on when this tool should be used instead of its siblings, nor any mention of prerequisites or exclusions. 'Evaluate an expression' implies a use case, but the description does not clarify when this is preferable to other evaluation or API-execution tools.

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