Cooling tower capacity evaluation: design vs test
Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {
"INPUT": "<INPUT>"
},
"name": "CTWRCAPADSNTST"
}
}| Name | Required | Description | Default |
|---|---|---|---|
| INPUT | Yes | ||
| OUTPUT | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure, yet it only restates the tool's purpose. It does not mention what is computed, side effects, return format, assumptions, or required conditions, leaving the agent to guess at behavior.
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 text is brief and front-loaded, but it is under-specified rather than efficiently informative. It reads more like a title than a description and does not include any explanatory sentences that would warrant a higher conciseness score.
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 tool with 20 required nested inputs, no output schema, and no annotations, a six-word phrase is drastically insufficient. There is no mention of units, engineering assumptions, how design and test inputs relate, or what output the agent can expect.
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%, and all properties are bare objects with no descriptions. The description provides no meaning for the 20 cryptic required fields (DSN_*, TST_*), so an agent cannot infer what values to supply.
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 the resource (cooling tower capacity) and the design-vs-test comparison, which is more specific than a bare title and helps distinguish it from sibling CTWR* tools. However, it uses a noun phrase ('Cooling tower capacity evaluation') rather than an explicit verb, preventing a 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?
There is no guidance on when to use this tool versus alternatives like CTWRCAPA or CTWRLG. The phrase 'design vs test' weakly implies a comparison use case, but no exclusions, prerequisites, or alternative selection criteria are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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