percentage_of

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

Annotations already declare the tool as read-only, non-destructive, and idempotent. The description does not add further behavioral details beyond the basic calculation, but it does not contradict annotations either.

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: a single sentence plus an example. It front-loads the purpose and provides immediate clarity with zero wasted words.

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 simple arithmetic tool with no output schema, the description is fully complete. It explains the function, how to use it with an example, and leaves no ambiguity about what the tool does.

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 0% description coverage (no descriptions for 'percent' or 'total'), so the description must compensate. It does so effectively by explaining via an example that 'percent' is the percentage value (e.g., 15) and 'total' is the base number (e.g., 200), making the parameters clear.

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 it calculates the percentage of a number, using a concise formula and example. It distinguishes from sibling tools like percentage_change and percentage_reverse by focusing on the basic 'X% of Y' operation.

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 implicitly indicates when to use this tool: to find what a given percentage of a total is. The example provides clear context. However, it does not explicitly exclude other percentage-related tools or state when not to use it.

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