number_converter

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

No annotations are provided, so the description must cover behavioral aspects. It mentions supported operations (convert, format, scientific, fraction), which is sufficient for a pure computation tool. It does not contradict any annotations (none present). However, it could mention error handling or input validation.

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: one sentence and two examples. It is front-loaded with the purpose and uses minimal words without sacrificing clarity.

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 5 parameters and no output schema, the description does not explain the return format or behavior for all operations. The examples imply a string output, but completeness could be improved by specifying output format for different operations.

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 100%, so baseline is 3. The description adds examples that demonstrate parameter usage, but does not provide additional semantic meaning beyond what the schema already conveys. The examples are helpful but not transformative.

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's purpose: 'Number format conversion tool, supporting base conversion, scientific notation, etc.' It provides examples that illustrate usage, effectively distinguishing it from sibling tools like unit_converter or basic_arithmetic.

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?

Examples show typical usage, but no explicit guidance on when to use this tool versus alternatives. The description does not mention prerequisites, exclusions, or context for choosing this tool over siblings like number_properties or expression_evaluator.

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