list_unit_conversions

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

With no annotations provided, the description carries the full burden. It discloses that the tool takes no arguments and returns a list of conversion objects, which is sufficient for a simple read-only list operation. It does not explicitly state side effects, but none are expected for a list call.

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 extremely concise, with three short lines covering usage timing, parameters, and an example. Every piece of text adds value; there is no fluff or repetition.

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 parameterless tool with an output schema available, the description provides all necessary context: when to use it, that it needs no arguments, and what the return shape looks like. This is complete and self-sufficient.

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 tool has zero parameters, so the baseline is 4. The description confirms 'Params: none,' which is all the parameter semantics needed. The input schema already reflects an empty parameter set.

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 lists unit conversions and explicitly frames it as a precursor to convert_unit. The example output shape (conversions[{id,from,to,…}]) makes the purpose concrete and distinguishes it from the sibling convert_unit tool.

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 gives explicit timing: 'before convert_unit' and when the conversion_id or unit pair is unknown. It does not list exclusions or alternative tools beyond convert_unit, but the context is clear enough for an agent to decide when to call it.

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