x402-tokenize
Tokenize: Split text into word tokens. Provide text or input; returns the array of whitespace-separated words. 🆓 5 free trial calls per signed wallet
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| text | No | ||
| input | No | ||
| lowercase | No |
Tokenize: Split text into word tokens. Provide text or input; returns the array of whitespace-separated words. 🆓 5 free trial calls per signed wallet
| Name | Required | Description | Default |
|---|---|---|---|
| text | No | ||
| input | No | ||
| lowercase | No |
Changes observed during successful MCP inspections.
Input schema / properties / input / descriptionRemoved value: -"Input to process"Input schema / properties / lowercase / descriptionRemoved value: -"Lowercase to process"Input schema / properties / text / descriptionRemoved value: -"Text to process"Input schema / properties / inputAdded value: +{
+ "description": "Input to process",
+ "type": "string"
+}Input schema / properties / lowercaseAdded value: +{
+ "description": "Lowercase to process",
+ "type": "string"
+}Input schema / properties / textAdded value: +{
+ "description": "Text to process",
+ "type": "string"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With zero annotations, the description carries the full behavioral burden, and it discloses only the return shape ("array of whitespace-separated words") plus a pricing note ("5 free trial calls per signed wallet"). It does not state what happens on empty input, whether both text and input can be supplied, or how the two aliases interact.
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?
Three short sentences with the action front-loaded and no filler; the return format follows immediately. The emoji-laden free-trial sentence is mild noise but still carries real payment context.
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?
There is no output schema, so the description usefully states the return value, which is the main thing it needs to supply. However, for a 3-parameter tool with 0% schema coverage and no annotations, it leaves unresolved alias/precedence behavior and the semantics of the lowercase flag.
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%, so the description must compensate for all three parameters, but it only names two of them (text, input) without explaining the aliasing or precedence rule. The third parameter, "lowercase," is entirely undocumented even though its string type for what is obviously a boolean flag makes correct invocation non-obvious.
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 opens with a specific verb and resource: "Split text into word tokens," which is far more concrete than the bare name x402-tokenize. It doesn't explicitly name a sibling it is not (word-count, sentence-split, chunk, word-frequency all remain plausible neighbors), 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?
"Provide text or input" is parameter guidance, not usage guidance: it never says when to pick this tool over x402-word-count, x402-sentence-split, or x402-chunk, despite an extremely dense sibling set of text utilities. There are no exclusions or preconditions of any kind.
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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