np_full

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

With no annotations, the description is the sole source of behavioral context. It only states what it does, not how it behaves (e.g., side effects, error conditions, that it returns a new array). The schema covers dtype defaults, but the description adds no extra behavioral traits.

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?

A single sentence that is direct and front-loaded. It earns its place by conveying the core purpose without extraneous words. Could potentially include a brief note about shape multi-dimensionality, but not necessary given schema.

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 presence of an output schema and well-documented input schema, the description is minimally sufficient. It lacks details about return values or practical usage tips, but for a simple function, it covers the essential purpose.

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 schema already documents all parameters adequately. The description adds no new semantic information beyond the schema, but the baseline is 3.

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?

Clearly states it creates an array filled with a constant value, which distinguishes it from siblings that create arrays with specific values (e.g., zeros, ones). The verb 'Create' and resource 'array' are specific. However, it could be more explicit about supporting multi-dimensional shapes.

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 like np_zeros, np_ones, or np_eye. The description assumes the user knows to use this for arbitrary constant values, but no explicit when/not or comparisons.

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