x402-validate
Validate: Validate input data against rules.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Type to process | |
| input | No | Input to process | |
| value | No | Value to process | |
| format | No | Format to process |
Validate: Validate input data against rules.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Type to process | |
| input | No | Input to process | |
| value | No | Value to process | |
| format | No | Format to process |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of explaining behavior. It only states that validation occurs, without disclosing how rules are specified, what outcome is returned, how failures are reported, or whether any side effects exist.
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 short but not effectively concise: the leading 'Validate:' is redundant with both the tool name and the rest of the sentence. The description is under-specified rather than tightly written, and it lacks the concrete details that would make the brevity valuable.
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 four optional parameters, no output schema, and a large family of closely related sibling tools, this description is far too incomplete. It does not explain what 'rules' means, how to invoke the validation, what inputs are valid, or what the result looks like.
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?
Although schema description coverage is 100%, every parameter description is a generic 'X to process' that adds little meaning. The description does not clarify the roles of type, input, value, and format, nor how they relate to the unspecified 'rules.' An agent cannot reliably determine which parameters to provide or how they interact.
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, 'Validate: Validate input data against rules,' essentially restates the tool name and provides only a generic action. It gives no indication of what kinds of data or rules are involved, and it does not differentiate itself from the many sibling validation tools such as x402-validate-email, x402-json-validate, or x402-schema-validate.
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?
The description offers no guidance about when to use this tool versus alternatives. There are no conditions, exclusions, or references to sibling validation tools, leaving an agent without enough information to decide whether x402-validate or a more specific validator is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The tool set is saturated with near-duplicates and synonyms: character-count vs char-count, clamp vs clamp-value, is-abundant vs is-abundant-num vs is-abundant-number, and fetch vs browser-scrape vs web-scrape vs text-scrape. Generic names like 'difference', 'normalize', 'range', and 'partition' make the boundaries even harder for an agent to determine.
Most tools share a x402- kebab-case prefix, but the set mixes noun-only names (math, hash, prime, time), verb-first names (get_stats, find, validate), auto-generated names (x402-publish-1787853294312-base-account), and inconsistent variants like temp vs temperature vs temperature-convert. This is not a coherent verb_noun convention despite the common prefix.
1677 tools is an extreme count that creates selection paralysis and makes coherent agent use impractical. A utility or marketplace server at this scale needs sub-services or namespacing rather than a flat tool list.
The surface has broad token coverage across many utility categories, but the marketplace aspect is incomplete: service_discovery and get_stats exist, yet there are no generic publish, update, delete, or account-management operations. Utility families also contain redundant variants without clear completion or lifecycle structure.