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

With no annotations, the description carries the full disclosure burden, but it only says 'Expression discarded'—which refers to a non-existent input and does not clarify side effects, return values, errors, or what happens to the nine actual parameters. The behavioral picture is essentially absent.

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 text is short, but this is under-specification rather than effective conciseness. 'Expression discarded' is cryptic and unhelpful, and the description omits critical invocation details rather than earning its brevity.

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 9 parameters, no annotations, and no output schema, this description is far too incomplete. An agent cannot determine what input to pass, what response to expect, or whether this tool is even functional for the advertised arithmetic purpose.

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 schema descriptions cover all 9 parameters, so the baseline is 3, but the description adds no meaning for any of them and instead introduces a phantom 'expression' not present in the schema. This actively undermines parameter understanding rather than supplementing it.

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 claims a specific capability, 'Evaluate a+b style arithmetic', but the input schema exposes nine unrelated string parameters (ref, url, city, feed, host, json, path, query) and no expression field. This makes the stated purpose misleading rather than clarifying, and it gives no basis for an agent to distinguish this from the sibling validation/check tools.

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 to use calc-eval versus any of the many sibling tools, and no prerequisites or exclusions. The only implied usage trigger is arithmetic evaluation, but the schema cannot actually support that invocation, making the guidance misleading.

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