mround

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

No annotations are provided, so the description carries full burden. It mentions 'standard rounding rules' which hints at behavior, but doesn't specify what those rules are (e.g., ties to even, away from zero), nor does it cover error handling, input constraints, or output format. For a tool with zero annotation coverage, this is insufficient behavioral disclosure.

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 two sentences: one stating the purpose and one providing domain/category context. Every word earns its place, and the core functionality is front-loaded. No wasted verbiage or redundancy.

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 coverage, and no output schema, the description is incomplete. It lacks details on rounding rules, parameter constraints, error cases, and return values. For a mathematical tool with two parameters, this leaves significant gaps in understanding how to use it effectively.

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 explains that 'number' is rounded and 'significance' is the multiple, adding meaning beyond the bare schema. However, it doesn't detail parameter constraints (e.g., significance must be positive), formats, or examples, leaving gaps. Baseline 3 is appropriate as it adds some value but not fully.

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 verb ('Round') and resource ('a number') with the specific mechanism ('to the nearest multiple of significance'). It distinguishes from siblings like 'round_number' by specifying the multiple-based rounding. However, it doesn't explicitly contrast with 'ceil' or 'floor' tools, keeping it at 4 instead of 5.

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 like 'round_number', 'ceil', 'floor', or 'ceiling_multiple'. It mentions the domain and category but offers no explicit when/when-not instructions or named alternatives, leaving usage context implied at best.

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