np_mod

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

No annotations are provided, so the description carries the full burden. It states 'element-wise' which indicates the operation applies per-element, but does not disclose behavior with zero divisors, data type handling, or output format. Minimal but not misleading.

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, direct sentence. No superfluous information, front-loaded with the core action. Every word earns its place.

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 simplicity of an element-wise modulo operation and the presence of an output schema (not shown but noted), the description is sufficiently complete. It communicates the essential behavior, though it could briefly mention the mathematical operation (e.g., computes a % b).

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 description coverage is 100% (both parameters have clear descriptions: 'First input array (dividend)' and 'Second input array (divisor)'). The description adds no additional meaning beyond what the schema already provides, so baseline score of 3 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 'Element-wise modulo of two arrays' uses a specific verb and resource, clearly stating it computes modulo element-wise. It distinguishes from sibling array operations like np_add, np_multiply, etc.

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 provides no guidance on when to use this tool versus alternative array operations (e.g., np_divide, np_remainder). No mention of edge cases like division by zero or integer overflow.

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