data_size

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions decimal (SI) and binary (IEC) representations, but it does not clarify how conversion works given the schema has no target-unit parameter — e.g., whether output returns all units or a single converted value. The '[PRO — 3 trial uses left]' prefix adds no behavioral clarity.

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 core description is a single concise sentence, but it is prefixed with irrelevant trial-usage text ('[PRO — 3 trial uses left]') that does not help an agent select the tool. The important semantic content is not front-loaded due to this noise, making it less effective than it could be.

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 simple tool with full schema coverage, the description covers the basic unit types, but it does not specify the output format or behavior when no target unit is provided. Since there is no output schema, the description should clarify what the conversion returns, and it remains ambiguous.

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 baseline is 3. The description repeats the unit list already in the enum and adds the decimal/binary context, but it does not add meaningful new semantics for the value parameter or clarify the missing target-unit behavior beyond what the schema provides.

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 uses a specific verb ('Convert') and resource ('data size units'), and clearly enumerates the unit scope (bytes, KB, MB, GB, TB, PB) plus decimal/binary representation. This is precise enough to distinguish it from sibling tools like byte_count or number_base.

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 purpose strongly implies it should be used when converting between data size units, but it does not explicitly state when to use it versus alternatives or mention any exclusions. There is no comparison to sibling tools such as byte_count, leaving usage context implicit rather than explicit.

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