verification_bottleneck

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

With no annotations provided, the description carries the behavioral disclosure burden. It goes beyond the schema by stating that all parameters are optional, that defaults mirror the interactive calculator at a specific URL, and that the response includes 'result, formula, interpretation and a ready-to-quote cite_as sentence.' This gives an agent useful expectations about calls and outputs.

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 three tightly worded sentences with no filler. It front-loads the core concept and computation, then covers defaults and output structure. Every sentence adds necessary information.

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 numeric calculator with six optional parameters, the description is nearly complete: it states the computation, gives defaults, references the source calculator, and describes the response contents. It does not discuss edge cases or constraints, but the schema already captures units and defaults, and the output is summarized sufficiently in the absence of an output schema.

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 coverage is 100%, with each parameter already documented by name, type, default, and units. The description adds that all parameters are optional but otherwise does not add meaning beyond the schema, so the baseline score of 3 is appropriate.

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 opens with 'Agents generate in parallel, humans review in series' and then specifies the exact computation: 'the real agent-fleet ceiling from review capacity, minutes per task and rework rate'. This is a specific verb plus resource, making the tool's purpose unmistakable even among the sibling calculator-style tools.

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 gives clear context by identifying the bottleneck scenario and the computed output, so an agent can infer when this tool applies. It does not explicitly name alternative tools or exclusion criteria, but the intended use case is clear enough without that.

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