convert_area

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool performs a conversion, which implies a read-only, non-destructive operation, but does not specify any behavioral traits such as error handling (e.g., invalid units), precision, or output format. For a tool with zero annotation coverage, this is a significant gap in transparency.

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 highly concise and front-loaded, consisting of a single sentence that directly states the tool's purpose with relevant examples. There is no wasted text, and it efficiently communicates the core functionality without unnecessary elaboration.

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, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose and hints at parameter semantics but lacks details on behavioral traits, full unit support, or error handling. Without annotations or output schema, it should do more to be complete, but it meets the minimum viable threshold.

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?

The input schema has 0% description coverage, so the description must compensate. It lists example units (square meters, square feet, acres, hectares, etc.), which adds meaning to the 'from_unit' and 'to_unit' parameters beyond the schema's string type. However, it does not detail the 'value' parameter or provide a full list of supported units, leaving some semantics incomplete. This partial compensation justifies a baseline score.

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 clearly states the tool's purpose: converting area between different units, with examples of units (square meters, square feet, acres, hectares). It specifies the verb ('convert') and resource ('area'), but does not explicitly differentiate from sibling tools like convert_length or convert_volume, which handle different types of conversions. This makes it clear but not fully sibling-distinctive.

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 alternatives. It mentions the domain (conversions) and category (general), but offers no explicit when/when-not instructions or references to sibling tools (e.g., convert_length for length conversions). This leaves usage context implied at best.

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