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

No annotations are present, so the description must carry the behavioral burden. It only says the expression is discarded, but it does not state whether a result is returned, whether the call is read-only, or what side effects occur—leaving the actual behavior ambiguous.

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 definition is short and front-loaded with its core purpose, and every word earns a place. It is slightly too terse to be excellent, but it avoids redundant restatement of the schema.

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?

With nine parameters, no annotations, and no output schema, the description is far too sparse to inform correct invocation. It does not explain the expression parameter, the return value, or how to choose among the many listed inputs.

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 coverage is 100%, but the description mentions 'a+b style arithmetic' while the input schema exposes parameters such as ref, url, city, feed, host, json, path, and query—none labeled as an expression. The description fails to map the intended operation onto any parameter and may confuse an agent trying to supply input.

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 names a specific operation ('evaluate a+b style arithmetic') and a clear resource, so an agent can tell it is a calculator-like tool. It does not explain what the result is or how the operation relates to the nine unrelated input parameters, and it does not differentiate from sibling validation 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 call calc-eval versus any sibling tool. It never names alternatives, required context, or exclusions, so an agent would choose it only by the tool name.

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