radix_convert

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

With no annotations, the description carries full responsibility for behavioral disclosure. It reveals that fractions are included, and bases that cannot represent a fraction are flagged as non-terminating. It also provides a concrete example call. It does not mention side effects (likely none) or error handling beyond flagging, but the core behavior is transparent.

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 two concise sentences, front-loaded with the main purpose and followed by a valuable example. Every sentence adds meaningful information, and there is no redundancy or filler.

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 (base conversion with fractions and non-terminating flagging) and the absence of an output schema, the description covers the essential behaviors and provides an example. It does not detail return values or error messages, but the conversion process is reasonably specified. The description falls short of a perfect score because it leaves parameter-specific details to the schema.

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 3 parameters with 0% description coverage, so the description must clarify each parameter. It only mentions the value and bases implicitly via the example 'radix_convert('zz', 36, 7)'. It does not explain the role of from_base vs to_base, their defaults, or that the value must be a string. The example partially illustrates parameter order but is ambiguous about which base is source vs target.

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 converts values between any bases 2..36, including fractions. It uses a specific verb ('convert') and a specific resource (value between bases), and the qualification 'ANY bases 2..36, fractions included' distinguishes it from sibling tools like base_repr or float_repr. The example call further clarifies the tool's scope.

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 implies usage for base conversion but does not explicitly state when to use this tool over alternatives like base_repr. It does not mention constraints or exclusions, though the scope (2..36, fractions) is clear. There is no guidance on when not to use it, leaving the agent to infer from the description alone.

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