log

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

With no annotations provided, the description carries full burden. It discloses key behavioral constraints (positive number requirement, base restrictions) and the default base value, which is valuable. However, it doesn't mention error handling, precision, or return format details that would be helpful for a mathematical operation tool.

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 appropriately sized with a clear purpose statement followed by parameter documentation. The Args section is structured but could be more integrated. Every sentence earns its place, though the formatting could be slightly more front-loaded with the core purpose.

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?

Given the mathematical nature, 2 parameters, 0% schema coverage, and existence of an output schema, the description provides good context. It covers purpose, parameter semantics, and constraints. The output schema existence means return values don't need explanation, making this reasonably complete for a mathematical function tool.

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?

With 0% schema description coverage, the description fully compensates by providing complete semantic information for both parameters: 'a' is 'the number to calculate logarithm for (must be positive)' and 'base' is 'the base of the logarithm (must be positive and not equal to 1, default is 10)'. This adds crucial meaning beyond the bare schema.

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 specific mathematical operation ('calculate the logarithm'), identifies the resource ('a number'), and distinguishes it from sibling arithmetic tools (add, subtract, multiply, divide, power) by focusing on logarithmic calculation rather than basic arithmetic or exponentiation.

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 usage context through the mathematical function name and parameter constraints, but doesn't explicitly state when to use this tool versus alternatives like 'power' for exponentiation or other mathematical operations. No explicit guidance on when-not-to-use or named alternatives is provided.

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