np_diff

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

With no annotations provided, the description bears full burden for behavioral disclosure. It fails to mention key traits such as edge-case behavior (e.g., empty arrays), resulting array length changes, or the requirement for numeric input. The single sentence is insufficient.

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, well-formed sentence with no superfluous content. It could benefit from additional context, but it is not verbose. Front-loading is appropriate.

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 tool's moderate complexity (3 parameters, output schema present), the description is minimal but sufficient for a basic understanding. However, it omits practical details like the effect of 'n' on output shape or data type requirements, leaving gaps for an AI agent.

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%, so baseline is 3. The description adds no extra meaning beyond what is already in the schema parameters. It does not elaborate on the 'n-th' concept or axis semantics beyond the schema defaults.

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 specifies the verb 'calculate', the resource 'n-th discrete difference', and the context 'along the given axis'. It clearly distinguishes this tool from siblings like np_subtract or np_gradient by naming the specific operation.

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 over alternatives, nor any mention of prerequisites or contraindicators. An agent would not know, for example, that np_diff reduces array length or that it is suited for numerical arrays only.

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