parse_numerical

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

No annotations are provided, so the description carries the burden of disclosing behavioral traits. It conveys that the operation is a parse/split step and implies a read-only preparatory action, but it does not state whether there are side effects, external calls, or failure behavior for non-numerical questions. This is a moderate gap, not a severe one.

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 two tight sentences with no filler. It front-loads the core behavior and then immediately gives usage context, making it easy to scan and act on.

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 one-parameter parsing tool with an output schema available, the description covers the essential guidance: what it parses, what it produces, and how it fits into the larger workflow. It does not cover edge cases or input quality constraints, but those are minor given the tool's simplicity and the output schema's expected presence.

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 for parameter meaning. It does clarify that the 'question' parameter is a counting/numerical question and indicates the resulting parsed components. The parameter itself is self-explanatory, which further reduces the need for detailed parameter documentation.

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 states a specific action (split) on a specific resource (a counting/numerical question) and names the four output components: target, attribute, relation, and anchor. It clearly differentiates the tool's role from siblings like count_in_view by framing it as the preparatory parsing step.

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 explicitly says to use this tool first on numerical questions and explains that its output feeds into grounding and count_in_view. It gives clear sequencing and context, though it does not explicitly state when not to use it or name alternative conditions.

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