x402-json-schema-validate
JSON Schema Validate: JSON Schema Validate
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| data | No | Data to process | |
| schema | No | Schema to process |
JSON Schema Validate: JSON Schema Validate
| Name | Required | Description | Default |
|---|---|---|---|
| data | No | Data to process | |
| schema | No | Schema to process |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure, and it discloses nothing: no mention of return format, error behavior, what happens on invalid input, or whether output is a boolean/report/error. The tautological text offers zero behavioral information.
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 description is short, but this is under-specification rather than conciseness — the single phrase earns no place because it conveys nothing beyond the name. There is no front-loaded useful content, just a redundant restatement.
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?
A two-parameter tool with no annotations, no output schema, and a tautological description is completely inadequate for an agent to invoke correctly. The agent cannot determine input formats, expected output, or how this differs from the multiple validation siblings in the same tool cluster.
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 coverage is 100%, so the baseline is 3 even though the tool description adds no parameter information. The schema's descriptions ('Data to process', 'Schema to process') at least label the two roles, but they are generic placeholders that omit expected formats (JSON string vs object), whether the schema must be a valid JSON Schema draft, and the relationship between the parameters.
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 'JSON Schema Validate: JSON Schema Validate' is a pure tautology that restates the tool name and title without adding any verb or resource detail. An agent learns nothing beyond what the name already conveys and cannot distinguish this tool from siblings like x402-json-validate, x402-schema-validate, or x402-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?
No guidance exists on when to use this tool versus the many closely related validation siblings (x402-json-validate, x402-schema-validate, x402-validate, x402-json-type). The description provides no context, prerequisites, or exclusions — there is nothing misleading, but also zero orientation.
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.