divmod_operation

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

No annotations are provided, so the description carries full burden. It states the tool performs division and returns two values, but doesn't disclose critical behavioral traits like error handling (e.g., division by zero), input constraints (e.g., integer vs. floating-point), or whether it's a pure mathematical function. For a tool with no annotations, this is a significant gap in transparency.

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 and front-loaded: the first sentence states the core functionality, the second clarifies the return format, and the third provides domain/category context. Every sentence earns its place 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?

Given no annotations, 0% schema description coverage, and no output schema, the description is incomplete. It doesn't explain parameter roles, error conditions, or detailed return format beyond '(quotient, remainder)'. For a mathematical tool with potential edge cases (like division by zero), this leaves significant gaps for an AI agent.

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 'division' but doesn't explain what parameters 'a' and 'b' represent (dividend and divisor), their expected types beyond the schema's 'number', or any constraints (e.g., b cannot be zero). The description adds 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 with specific verbs ('perform division') and resources ('return both quotient and remainder'), and distinguishes it from sibling tools like 'divide' (which likely returns only quotient) and 'remainder' (which likely returns only remainder). The explicit mention of returning both values makes the purpose unambiguous.

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 for arithmetic division with both quotient and remainder needed, but doesn't explicitly state when to use this tool versus alternatives like 'divide' or 'remainder' from the sibling list. The domain/category tags provide some context, but no explicit guidance on selection criteria is given.

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