is_coprime

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

No annotations are provided, so the description carries the full burden. It states what the tool does (checking coprimality) but doesn't disclose behavioral traits like input constraints (e.g., handling of negative numbers, zero, or large integers), performance characteristics, error handling, or output format. The description is purely functional without operational context.

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 efficiently structured in a single sentence with parenthetical clarification and domain/category tags. It's front-loaded with the core purpose and avoids unnecessary verbiage. The domain/category could be considered slightly extraneous but adds useful context without significant bloat.

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 (2 parameters, no annotations, no output schema), the description is minimally adequate but lacks completeness. It doesn't explain what the output will be (e.g., boolean true/false, or a structured result), doesn't cover edge cases, and provides no examples. For a mathematical tool, more operational context would be helpful despite the straightforward function.

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 0%, so the description must compensate. It mentions 'two numbers' which aligns with parameters 'a' and 'b', but doesn't add meaning beyond what's obvious from the schema (two integers). No details about parameter interpretation (e.g., order matters, valid ranges) are provided. With 0% coverage and minimal parameter clarification, this meets the baseline for adequate but incomplete documentation.

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 with a specific verb ('Check') and resource ('if two numbers are coprime'), and provides the mathematical definition ('their greatest common divisor is 1'). It also includes domain/category context ('Domain: arithmetic, Category: number_theory') that helps distinguish it from sibling tools, though not by direct comparison.

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 provides no guidance on when to use this tool versus alternatives. While the domain/category hints at context, it doesn't explicitly state when this tool is appropriate or when other tools (like 'gcd' or 'is_prime') might be better choices. No usage boundaries or prerequisites are mentioned.

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