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

With no annotations, the description carries the full behavioral burden. It usefully discloses the per-candidate full-design execution, four output metrics, and automatic vessel sizing, but does not address side effects, candidate failure handling, or the potentially greater computational cost of multiple design runs.

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?

Two compact sentences front-load the purpose, inputs, processing model, and outputs, then provide the selection use case and defaulting behavior. There is no filler, and the technical details remain easy to scan.

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?

Because there is no output schema, listing feed pressure, permeate TDS, average flux, and specific energy consumption is particularly valuable. Together with the fully documented nested input schema, this is enough for correct invocation, though explicit single-design routing and failure or performance behavior would improve completeness.

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%, establishing a baseline of 3. The description adds the practical 2–5 candidate scope and clarifies how candidates are evaluated under common water and design inputs, although the vessels default and target-flux details largely repeat the 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 identifies a multi-candidate design comparison, states that a complete design is run for each candidate element or arrangement, and names the compared metrics. This clearly distinguishes it from single-design execution and from the water and scaling analysis siblings.

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?

It gives a concrete use case—comparing candidates during element selection—and recommends comparing 2–5 candidate elements. It does not explicitly route single-candidate requests to run_design or identify other situations where a sibling tool would be preferable.

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