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

No annotations are provided, but this is a pure deterministic string transform with no side effects, auth, or state to disclose. The description signals the operation is a simple conversion and the examples reveal the output format, but it doesn't explicitly state determinism, error behavior for non-integers, or handling of edge cases like large or negative numbers.

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 front-loaded sentence with zero filler; the parenthetical examples add disambiguation rather than padding, so every token 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?

For a no-annotation, no-output-schema scalar transform, the description gives the essential input type and expected output shape via examples. It is nearly complete, with only minor gaps around edge-case handling and the nested payload structure.

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 0% and the single parameter is nested inside a 'payload' wrapper whose internal 'value' field is undocumented. The description clarifies that the input is an integer, which partially compensates, but it does not explain the payload envelope or value constraints, leaving a gap the schema does not fill.

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?

States a specific verb (Convert) and resource (integer to English ordinal form), and the parenthetical examples (1st, 2nd, 3rd, 11th, 21st) pin down exactly what 'ordinal form' means including the irregular teens. This clearly distinguishes it from siblings like number_words, number_roman, and number_radix.

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 versus alternatives such as number_words (spelled-out numbers) or number_roman. The purpose implies a usage context but there are no explicit conditions, prerequisites, or exclusions to help an agent route between the number-formatting siblings.

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