encode_radix

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

No annotations are provided, so the description must fully disclose behavior. It mentions base range and large-number support but omits details like output format (case of letters for bases >10), handling of negative numbers, or whether non-integer inputs are accepted. This is a minimal disclosure for a tool with no safety annotations.

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 a single sentence plus a clarifying example. It is front-loaded with the verb and resource, and every word contributes information. No fluff.

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 relatively simple conversion tool with no output schema and partial parameter descriptions, the description covers core usage. However, missing behavioral details (output casing, precision limits, error cases) leave some gaps, though the example mitigates ambiguity.

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 coverage is only 33% (only 'value' has a description), but the tool's description includes a worked example that conveys the role of all three parameters. It also reinforces the base range already present in the schema, adding meaning to from_base and to_base.

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 numbers between arbitrary bases (2-36) and supports large numbers, with a concrete example. This distinguishes it from encoding tools like encode_base64 or encode_url, which handle text/byte encodings.

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?

Usage context is implied by the description (convert between number bases), but there is no explicit 'when to use' or comparison with alternatives. The example provides practical guidance but no exclusionary criteria.

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