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

Since no annotations are provided, the description effectively discloses the core behavior: simplification using GCD. It is a pure computation with no side effects or destructive actions, which is adequately communicated.

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 with two sentences, front-loading the purpose. However, the incorrect mention of an optional parameter wastes space and reduces 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?

For a simple tool with output schema, the description covers the basic behavior and use cases. However, the error regarding optional parameters and lack of detail on output format or constraints (e.g., positive integers) leave gaps.

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 description introduces confusion by mentioning an optional parameter 'c' that does not exist in the schema, and uses labels 'a' and 'b' instead of the actual parameter names 'numerator' and 'denominator'. Schema coverage is high, but the description adds misleading information.

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 simplifies a ratio to lowest terms using GCD and provides use cases like proportions, mixing, or scaling. However, it does not explicitly differentiate from sibling tools like calculate_fraction, which might be similar.

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 gives contexts for use (proportions, mixing, scaling) but lacks when-not-to-use guidance or explicit alternatives. It only references list_bundles for related calculators, which is vague.

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