convert_weight

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 conversion action but lacks details on error handling (e.g., invalid units), precision, rounding, or output format. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 concise and front-loaded, stating the core function in a single sentence. The domain/category note adds minimal but relevant context without redundancy. It avoids unnecessary elaboration, making it efficient for quick understanding.

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 complexity (3 parameters, no output schema, no annotations), the description is incomplete. It lacks details on parameter usage, behavioral traits, and output expectations. For a conversion tool with multiple inputs, more context is needed to ensure correct invocation and result interpretation.

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, and the tool description does not explain the parameters. It mentions units like kilograms and pounds but does not clarify the expected format for 'from_unit' and 'to_unit' (e.g., abbreviations, case sensitivity) or the meaning of 'value'. With low schema coverage, the description fails to compensate, leaving parameters poorly defined.

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 weight/mass between units like kilograms, pounds, ounces, and grams. It specifies the verb ('convert') and resource ('weight/mass'), making the function evident. However, it does not explicitly differentiate from sibling tools like convert_length or convert_temperature, though the domain/category hints at specialization within conversions.

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 and category but does not specify scenarios, prerequisites, or exclusions. Without explicit usage context, the agent must infer applicability from the tool name alone.

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