x402-random-phone
Random Phone: Generate a random phone.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| n | No | N to process | |
| value | No | Value to process |
Random Phone: Generate a random phone.
| Name | Required | Description | Default |
|---|---|---|---|
| n | No | N to process | |
| value | No | Value to process |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description must disclose behavioral traits itself. It only states that a random phone is generated, with no mention of format, country code, length, determinism, or any side effects. The behavior is minimally disclosed but almost entirely unspecified.
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 very short, but it mostly restates the tool name and title. The single sentence does not earn its place because it carries almost no operational information; this is under-specification rather than effective conciseness.
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 no output schema, no annotations, and two confusingly described parameters, the description omits essential context: what input the parameters control, what format the generated phone takes, and what the return value looks like. The description is not complete enough for an agent to invoke the tool confidently.
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%, both parameter descriptions ('N to process' and 'Value to process') are generic placeholders that do not explain their relevance to generating a random phone. The tool description adds no meaning to these parameters, and the agent cannot infer what values to supply or whether they are optional.
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 a specific action ('Generate a random phone') and names the resource ('phone'). It is distinguishable from many siblings because it explicitly mentions random generation and phone, but it does not clarify whether 'phone' means a phone number, device identifier, or something else, and does not differentiate it from related random-family tools.
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 is provided about when to use this tool versus alternatives such as x402-random-number, x402-is-phone, x402-mask-phone, or x402-validate-phone. The description gives no context, prerequisites, or exclusion criteria, leaving the agent to guess the appropriate use case.
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.