logarithm

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

With no annotations provided, the description carries the full behavioral burden and does reasonably well. It discloses that invalid inputs raise ValueError, that the operation is logged, and that the result is returned in a dictionary, providing useful behavior beyond the schema.

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 well-structured with Args, Returns, Raises, and Notes sections, and the core purpose is front-loaded in the first sentence. Each section adds useful detail without significant redundancy, though some repetition with the schema is present.

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 description covers the expected inputs, error behavior, default configuration, natural logarithm alternative, return shape, and logging side effect. It is complete enough for a simple mathematical operation, though it could be improved by defining what makes a base 'invalid' and by referencing the natural_log sibling.

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 reported as 0%, so the description must compensate. It explains that value must be positive, that base defaults to 10, that base 'e' performs natural logarithm, and that invalid bases raise an error. This adds meaningful semantic information beyond the raw schema types.

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 operation: 'Calculate the logarithm of a value with a specified base,' with the tool name and resource clearly aligned. It does not explicitly distinguish itself from the sibling natural_log tool, though the natural logarithm handling is mentioned indirectly via base 'e'.

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?

No explicit guidance is given about when to choose logarithm over natural_log or other math siblings. The note about base 'e' implies how to do natural logs, but it does not tell an agent when to use this tool versus the dedicated natural_log sibling.

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