power

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

The description discloses the return type (a string) and a specific edge case where an error may occur (e.g., negative base with fractional exponent). This provides useful behavioral context beyond the basic operation, though it does not enumerate all potential edge cases.

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 brief and well-structured, with clear sections for the operation, arguments, and return value. Every sentence adds value and there is no redundant or extraneous information.

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 is complete for the tool's complexity: it explains the operation, the arguments, the return format, and a notable error condition. An agent has sufficient information to invoke the tool correctly.

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?

Both parameters (base and exponent) are described in plain language in the description, fully complementing the input schema. The schema coverage is 100%, and the descriptions add clear meaning about what each parameter represents.

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's purpose: 'Raise a number to a power.' This unambiguously distinguishes it from sibling tools like add, subtract, multiply, divide, square_root, and percentage.

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 explains what the tool does but does not explicitly mention when to use it over alternatives or when not to use it. It is self-explanatory enough for a straightforward math operation, but it lacks explicit guidance on choosing it among siblings.

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