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

Annotations already declare readOnlyHint and idempotentHint, so safety behavior is covered. The description adds meaningful context beyond those annotations: 'Arbitrary precision via BigInt, so large values stay exact' and the integer-only constraint. This enriches the behavioral model without contradicting the structured metadata.

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?

Three sentences total, front-loaded with a clear purpose statement followed by precision detail and a usage directive. No wasted words; every sentence earns its place.

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?

The tool is simple, annotations confirm it is read-only and idempotent, and an output schema exists (so return format is already covered). The description covers scope, precision, examples, and usage guidance, making it complete for an AI agent to select and invoke the tool confidently.

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%, with each parameter fully described (value as string, from_base with default 10, to_base with default 16). The description reinforces this with examples but does not add syntax or format details beyond what the schema already provides. The arbitrary precision note about large values adds a small layer of contextual meaning.

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 opens with a specific verb ('Convert') and resource ('integer between number bases 2–36'), then gives concrete examples (hex to binary, decimal to base-36). This clearly distinguishes it from sibling tools like unit_convert, which handle physical unit conversions rather than radix 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 final sentence, 'Use for radix conversions instead of doing them by hand,' explicitly states when to use the tool. It provides context through the base range and integer scope, though it does not explicitly mention when not to use it or name alternatives, which keeps it from a 5.

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