np_subtract

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

With no annotations, the description carries full burden for behavioral traits. It only states 'element-wise subtraction' without disclosing edge cases (e.g., broadcasting, type promotion, or error conditions). This is minimal and insufficient for a robust disclosure.

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 a single sentence that directly states the purpose. It is concise, front-loaded, and contains no unnecessary words.

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?

For a simple element-wise subtraction tool, the description covers the essential purpose. The existence of an output schema (per context) likely handles return value details, so completeness is adequate but could mention broadcasting or return type.

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 the baseline is 3. The description adds no meaning beyond the schema's parameter descriptions ('First input array.', 'Second input array.'). It does not enrich the parameter semantics.

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 'Element-wise subtraction of two arrays' uses a specific verb ('subtraction') and resource ('two arrays') that clearly states the tool's purpose and distinguishes it from siblings like np_add.

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 does not provide explicit guidance on when to use this tool versus alternatives like np_add or np_divide. However, the name and description are self-explanatory for a common operation, making usage context implied rather than explicit.

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