percentage

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what calculations are performed but does not describe behavioral traits such as error handling (e.g., division by zero), input validation, output format, or performance characteristics. The description is functional but lacks transparency about how the tool behaves beyond its basic purpose.

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, efficient sentence that front-loads the core purpose ('Calculate percentages') and then specifies the exact operations without any wasted words. It is appropriately sized for a straightforward mathematical tool and every phrase contributes to understanding its function.

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 low complexity (basic calculations), high schema coverage, and no output schema, the description is adequate but has gaps. It covers the purpose and operations but lacks details on behavioral aspects like error handling or output format, which are important for an agent to use it correctly without annotations. It is minimally viable but could be more complete.

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 input schema has 100% description coverage, with clear parameter names and an enum for 'operation' that aligns with the calculation types in the description. The description adds minimal value beyond the schema by listing the operations, but it does not provide additional context like examples, formula details, or parameter relationships. Baseline 3 is appropriate as the schema does the heavy lifting.

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 specific verbs ('calculate percentages') and enumerates the exact types of calculations it performs (percentage of a number, percentage increase/decrease, what percentage X is of Y). It distinguishes itself from sibling tools like 'calculate' (general), 'convert_units', 'solve_equation', 'statistics', and 'trigonometry' by focusing exclusively on percentage operations.

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 by listing the calculation types, but it does not explicitly state when to use this tool versus alternatives like the general 'calculate' tool or other mathematical siblings. There is no guidance on prerequisites, exclusions, or specific contexts where this tool is preferred over others.

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