isnumber

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

With no annotations, the description carries the full burden of behavioral disclosure. It adds the important detail that numbers inside strings (e.g., "123") are not considered numbers, which is beyond a generic 'validates a value is a Number.' It doesn't mention return type, but that's inferable from 'validates.'

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 concise with only two short sentences. The first sentence states the core purpose, and the second provides a critical edge case. Every word earns its place, and no unnecessary detail is present.

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 simplicity (no parameters, no output schema, many similar siblings), the description is complete enough. It clearly explains the tool's behavior and the key nuance (strings not counted), enabling the agent to select it correctly among sibling type-checkers.

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 tool has zero parameters, so parameter semantics are not applicable. Per the instructions, a baseline of 4 is appropriate when there are no parameters, and the description need not add parameter-specific 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 clearly states the tool validates that a value is a Number, with a specific verb and resource. It also distinguishes itself from sibling type-checkers by explicitly noting that numbers inside strings are not considered valid, which is a key behavioral detail.

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 through its definition of strict numeric validation, but it does not explicitly state when to use this tool versus alternatives like 'isstring' or 'isarray'. It gives context about the strict checking but lacks explicit when-to-use guidance.

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