calculate_logarithm

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

No annotations are provided, so the description must carry the full burden. It states the return format as {result} but does not disclose behavior for invalid inputs (e.g., negative values, edge cases). The schema shows a minimum for value, but this is not mentioned in the description.

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 concise with two sentences, lacking any verbose or redundant text. It is front-loaded with the primary action and supported bases.

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?

With an output schema present, return value description is covered. However, the description lacks context for when to choose this tool over numerous sibling calculate_ tools. It provides a cross-reference to related calculators but insufficient explicit guidance.

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 coverage is 100%, so baseline is 3. The description reiterates the base options (natural, common, binary) already present in the schema and mentions the return format, adding minimal value beyond the 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 'Calculate logarithm in any base' and specifies the supported bases (natural, common, binary). The verb 'Calculate' and resource 'logarithm' are specific, and the tool name aligns perfectly. Although sibling differentiation is not explicit, the purpose is unmistakable.

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 mentions 'See list_bundles for related 'math' calculators,' which hints at alternatives but does not explicitly state when to use this tool versus other calculate_ tools. It provides no exclusion criteria or specific context for selection.

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