x402-returns
Returns: Calculate period-over-period returns of a price series. Provide values array; returns percentage changes between consecutive items.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| values | No | Values to process |
Returns: Calculate period-over-period returns of a price series. Provide values array; returns percentage changes between consecutive items.
| Name | Required | Description | Default |
|---|---|---|---|
| values | No | Values to process |
Changes observed during successful MCP inspections.
Input schema / properties / valuesAdded value: +{
+ "description": "Values to process",
+ "type": "string"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, and it does disclose the core behavior: percentage changes between consecutive items, which tells the agent the output length differs from the input. It omits error/edge handling (single value, empty input, zero denominators) and any statement about side effects, which matters for a tool with zero annotation coverage.
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 with the operation front-loaded and no filler. The redundant 'Returns:' prefix merely repeats the tool name and could be dropped, but nothing else is wasted.
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 single-parameter pure computation with no output schema and no annotations, the description conveys the operation and the shape of the result. It is still missing the input encoding (string vs array), output length semantics (n-1 items), and degenerate-input behavior, which are the details an agent would need to call it correctly.
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 does add real meaning by specifying the values are a price series (not arbitrary numbers), but it calls them a 'values array' while the schema types the parameter as a string, a mismatch that slightly muddies rather than clarifies input format.
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 ('Calculate period-over-period returns of a price series') and states the transformation, so the agent knows exactly what the tool computes. However, it never distinguishes itself from close siblings such as x402-log-returns, x402-percentage-change-array, or x402-rate-of-change, so sibling selection is left to inference.
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 explicit when-to-use guidance and no naming of alternatives. 'Provide values array' is input instruction, not a condition for choosing this tool over log-returns or a plain percent-change tool, so an agent cannot tell which return flavor is appropriate.
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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