evaluate_math

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

The description includes 'safely' but does not explain what safety measures are taken (e.g., sandboxing, error handling). Annotations indicate readOnlyHint=false, implying potential side effects, but the description gives no behavioral details. For a mutation tool, this lack of transparency is a gap.

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 very concise: a single sentence of 5 words. Every word earns its place, providing the essential purpose and a key trait (safety). No superfluous content.

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?

The tool has one parameter and no output schema. The description lacks information about the return format (e.g., numeric, string), error behavior, or edge cases. It is adequate but could be more complete by mentioning what the result looks like.

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 input schema fully covers the parameter with a clear example. The description adds 'safely' but no additional semantic meaning beyond the schema. With 100% schema coverage, baseline is 3; the description does not go beyond.

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 clearly states the tool evaluates mathematical expressions, using a specific verb (evaluate) and object (mathematical expressions). It distinguishes itself from siblings like calculate_percentage by focusing on arbitrary expressions.

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 description provides no explicit when-to-use or when-not to use guidance, nor does it mention alternatives. However, the purpose is clear enough that an agent can infer usage context. An explicit mention of supported operations or limits would improve this.

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