x402-json-validate
JSON Validate: Validate + pretty-print JSON. ๐ 5 free trial calls per registered wallet
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| input | No | Input to process |
JSON Validate: Validate + pretty-print JSON. ๐ 5 free trial calls per registered wallet
| Name | Required | Description | Default |
|---|---|---|---|
| input | No | Input to process |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the core behavior (validate + pretty-print) and adds a free-trial/wallet constraint, but it does not explain what happens on invalid JSON, what the output looks like, or whether both operations happen together.
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 and front-loaded, with the purpose stated first and the billing/trial note earning its place. However, 'JSON Validate:' is largely redundant with the tool name.
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 simple one-parameter utility, the description communicates the main operation and a usage constraint. Yet with no output schema and no guidance on invalid input or return format, the agent still has to infer important calling details.
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. The single parameter 'input' is only described as 'Input to process', which is generic; the tool description adds that it should be JSON, but no concrete syntax, format, or example is provided.
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 clearly states the tool's verb and resource: it validates and pretty-prints JSON. The dual function helps distinguish it from single-purpose siblings like x402-is-json or x402-json-pretty, though no sibling is named and the 'JSON Validate:' prefix repeats the tool name.
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 usage guidance is provided. The sibling list contains many JSON-related tools such as x402-json-format, x402-json-pretty, x402-is-json, and x402-json-schema-validate, but the description gives no explicit context for when to choose this one over those alternatives.
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.