verify_hydraulic_boundary

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

No annotations are provided, so the description carries the full burden. 'Calculates' reasonably implies a pure, side-effect-free computation, and the description does disclose the four result categories it produces, but it never explains what optional inputs like measured_flow_lpm do (presumably a measured-vs-required comparison, given the tool name 'verify'), nor any error/validity conditions or output shape.

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?

A single front-loaded sentence with no filler; the computed outputs are listed compactly. Its only structural weakness is that it packs four result types into one clause, leaving no separate sentence for scope or behavior.

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?

With five parameters, no annotations, and no output schema, the description should do more: it lists what is computed but not how results are returned, and it leaves the 'verify' framing of the tool name unexplained relative to its stated 'calculates' behavior. The rich schema offsets the parameter gap, keeping this at a minimum-viable level.

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 100% — every parameter, including units, ranges, enum values, and defaults, is documented in the schema. The description adds essentially no parameter-level meaning beyond restating the computed quantities, so the baseline 3 applies.

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 names a specific verb ('Calculates') and enumerates concrete resources/outputs: coolant flow rate, mass balance, heat removal capacity, and ASHRAE Liquid Cooling Class compliance, scoped to AI compute racks with a concrete example (GB200 NVL72). That makes the tool clearly distinguishable by subject matter from siblings like calculate_pipe_friction_loss or classify_corrosion_severity, though it never explicitly contrasts itself with them.

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?

Usage is only implied by the domain phrase 'for AI compute racks (e.g., NVIDIA GB200 NVL72)' — an agent can infer this is for liquid-cooled AI rack verification, but there is no explicit when-to-use statement, no mention of when NOT to use it, and no pointer to calculate_pipe_friction_loss or other siblings for related calculations.

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