x402-liters-to-gallons
Liters To Gallons: Convert liters to gallons.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| value | No | Value to process | |
| liters | No | Liters to process |
Liters To Gallons: Convert liters to gallons.
| Name | Required | Description | Default |
|---|---|---|---|
| value | No | Value to process | |
| liters | No | Liters to process |
Changes observed during successful MCP inspections.
Input schema / properties / litersAdded value: +{
+ "description": "Liters to process",
+ "type": "string"
+}Input schema / properties / valueAdded value: +{
+ "description": "Value to process",
+ "type": "string"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It does not disclose input format expectations (e.g., numeric strings), output format or precision, error handling, or any other runtime behavior. It merely restates the conversion operation.
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 single sentence is front-loaded and wastes little space. It slightly repeats the tool name pattern ('Liters To Gallons: Convert liters to gallons'), but it remains efficient and readable.
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 conversion tool with no output schema and no annotations, the description is too sparse. It does not explain what the tool returns, how the result is formatted, or what input types are accepted. An agent can infer the operation but lacks enough context to invoke it confidently with the ambiguous 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 description coverage is 100%, so the baseline is 3. The description adds no meaning beyond the schema; it does not clarify the ambiguous duplicate-like parameters ('value' and 'liters') or explain which one is actually expected. The structured schema remains the primary source of parameter information.
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 states a specific verb and conversion pair: 'Convert liters to gallons.' This clearly distinguishes the tool from a generic converter and implies the sibling x402-gallons-to-liters by inversion. It does not explicitly name the sibling, so it falls short of 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?
No when-to-use guidance is provided. The description does not mention prerequisites, alternatives, or conditions for choosing this tool over the reverse conversion or a generic unit converter. Usage is only implied by the tool name and description.
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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