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

Annotations already declare the operation as read-only, idempotent, open-world, and non-destructive. The description adds useful behavioral details beyond annotations: the -1 fallback when no greater element exists and the 1-credit cost. It does not cover edge cases such as duplicates or empty input, so it stops short of a 5.

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 three compact sentences, front-loads the core algorithm, and includes the return fallback and cost without wasted wording. Every sentence adds useful information.

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 low-complexity single-parameter computation, the description covers the operation, fallback return value, and credit cost. It does not fully specify the output shape or clarify the schema's string/array input union, which keeps it from a 5.

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 the single nums parameter is already documented in the schema. The description refers to a list but adds no syntax, format, or edge-case meaning beyond the schema, making the baseline 3 appropriate.

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 states a specific algorithm with a clear verb and resource: it finds the next greater element to the right for each list element. This clearly distinguishes it from other algorithmic siblings such as find_peak_element or find_majority_element.

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 explains what the tool computes but gives no explicit guidance on when to use it versus alternatives. There are no exclusions, prerequisites, or sibling comparisons.

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