List standard paper sizes with dimensions in mm and inches. Pure CPU, instant.
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": {
"series": "<series>"
},
"name": "paper_sizes"
}
}| Name | Required | Description | Default |
|---|---|---|---|
| series | Yes | A, B, C or US |
Changes observed during successful MCP inspections.
Input schema / properties / seriesAdded value: +{
+ "description": "A, B, C or US",
+ "type": "string"
+}Input schema / requiredAdded value: +[
+ "series"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the behavioral burden; 'Pure CPU, instant' usefully signals a local, non-network, fast read operation. However, it does not say whether the result is a fixed static table, whether all sizes in a series are returned, or whether output is sorted, which matters for a listing tool.
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 short, front-loaded sentences with no filler; the output units come first and the performance note second. Slightly terse given there is room for one more clarifying clause without bloating.
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 trivial single-parameter lookup with no output schema, the description states the resource, the units, and the cost profile — enough to call it correctly. Only the shape of the returned list (all series sizes, ordering) is left implicit.
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% and the single parameter is documented as 'A, B, C or US', so the schema does the heavy lifting. The description adds nothing about the series parameter or how it affects output, 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 and resource ('List standard paper sizes') and states the units returned (mm and inches), so the agent knows exactly what the tool produces. It does not differentiate from the nearby sibling 'page_size', which an agent could plausibly confuse with a paper-dimension lookup.
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 such as 'page_size' or 'pixel_convert'. The description gives no conditions, prerequisites, or exclusions — only a restatement of what it outputs.
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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