fmod

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. While it mentions the operation is 'similar to % but for floats', it doesn't describe edge cases (e.g., division by zero, NaN handling), precision considerations, or what the output looks like. For a mathematical operation tool with zero annotation coverage, this leaves significant behavioral gaps.

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 with just two sentences that directly state the purpose and provide a helpful analogy. Every word earns its place, and the information is front-loaded with no unnecessary elaboration.

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 mathematical operation tool with 2 parameters, 0% schema description coverage, no annotations, and no output schema, the description is insufficient. It doesn't explain parameter roles, edge case behavior, return format, or how it differs from similar sibling tools. The domain/category tags help somewhat, but don't compensate for the missing operational details.

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 for its two parameters (x and y), and the description doesn't explain what these parameters represent. However, given the tool's name 'fmod' (common for floating-point modulo) and the description's reference to similarity with '%', an experienced user might infer x is the dividend and y is the divisor. This provides minimal semantic value beyond the bare schema.

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: 'Calculate floating-point modulo operation' with the specific verb 'calculate' and resource 'floating-point modulo operation'. It distinguishes from the standard modulo operator by specifying 'Similar to % but for floats', though it doesn't explicitly differentiate from sibling tools like 'modulo' or 'remainder' which might handle different numeric types.

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 implied usage guidance through the phrase 'Similar to % but for floats', suggesting this tool should be used for floating-point modulo calculations rather than integer modulo. However, it doesn't explicitly state when to use this versus alternatives like 'modulo' or 'remainder' tools in the sibling list, nor does it mention any prerequisites or exclusions.

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