calculate_rule_of_three

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

No annotations are provided, so the description must convey behavioral traits on its own. It states the tool is for solving cross-multiplication and returns a value, but does not disclose potential issues like division by zero, input validation, or that it is read-only (likely harmless). This is insufficient transparency for a calculation tool with no annotation support.

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 extremely concise: two sentences front-load the purpose and usage, with no redundant information. Every word contributes to understanding, and the cross-reference to list_bundles is efficiently placed.

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 mathematical tool, the description covers core purpose, use cases, and a pointer to related calculators. However, it misses edge cases (e.g., zero values), does not explain the return value format beyond 'x', and the output schema (though present) is not used to reduce burden. Given the mismatch and lack of error handling mention, completeness is adequate but not thorough.

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 100% (all parameters have basic descriptions), but the description contradicts the schema by mentioning input 'c' while schema uses 'x' as a required input. This mismatch undermines parameter semantics. The description does not clarify the relationship between 'c' and 'x', nor does it provide context beyond the schema's generic labels ('Known value A').

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 solves rule-of-three/cross-multiplication for proportions, with use cases like recipe scaling and unit pricing. However, it mentions input 'c' while the schema uses 'x', creating confusion. The sibling reference to list_bundles provides category context but does not explicitly differentiate from other calculation 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?

Provides explicit use cases (proportions, recipe scaling, unit pricing) and hints at related calculators via list_bundles. However, it lacks guidance on when not to use this tool versus alternatives like calculate_percentage or calculate_ratio_simplify, and does not name specific sibling alternatives.

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