logarithm

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

No annotations are provided, so the description carries the behavioral disclosure burden. It does disclose that the input number must be positive, which is useful, but it does not mention base validity constraints (e.g., base > 0 and base ≠ 1), edge cases, or error behavior. This is a meaningful but incomplete disclosure.

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 a single front-loaded sentence with no filler. It conveys the operation, the primary constraint, and the parameter role efficiently.

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 is simple and has an output schema, so return-value documentation is not required in the description. The main gap is the missing base domain and error semantics, which could lead to invalid calls. Overall, the description is adequate but not fully complete for a no-annotation environment.

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 0%, so the description must add meaning to the parameters. It does clarify that 'number' is the positive input and that 'base' is the logarithm base, which goes beyond the bare schema types. However, it does not explain valid base values or how defaults behave, so the parameter guidance is still partial.

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 states a specific verb ('Calculate') and a specific resource ('logarithm'), and it adds the key constraints 'positive number' and 'specified base'. It clearly distinguishes this tool from the arithmetic sibling tools such as power, square_root, and nth_root.

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 implies the use case: call this when a logarithm is needed. However, it provides no explicit guidance about when not to use it or how it compares to related inverse operations like power or nth_root. The usage context is clear but not explicitly framed.

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