np_abs

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

The description indicates the core operation but does not disclose behaviors for edge cases like NaN, complex input, or integer overflow. With no annotations, it carries the full burden and only partially meets it.

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?

Single sentence, front-loaded with the verb and resource, no wasted words. Perfectly concise for the scope.

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 available and only one parameter, the description is largely complete. However, it could mention return type behavior (e.g., same shape as input) or data type handling.

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% with a single parameter described as 'The input array.' The tool description adds no additional meaning beyond this; baseline score applies.

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 computes absolute values of array elements, using the specific verb 'calculate' and resource 'absolute value of array elements', distinguishing it from mathematical siblings like np_add or np_sin.

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 guidance on when to use this tool versus alternatives (e.g., np_negative, np_sign), or what types of inputs are suitable (e.g., real vs complex numbers).

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