x402-km-to-miles
Km To Miles: Convert km to miles.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Km To Miles: Convert km to miles.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 behavioral disclosure. It only states the conversion and says nothing about how input is supplied, what the output looks like, or any precision or edge-case behavior. The empty input schema makes this gap critical—an agent cannot infer the invocation mechanism.
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, but it mostly repeats the tool name: 'Km To Miles:' followed by 'Convert km to miles.' There's no wasted wording, but there's also no added value beyond the 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?
With no annotations and no output schema, the description must explain both input and output. It does neither. The empty schema leaves an agent completely unable to determine how to call the tool, and the return value is never described. This is a non-informative stub.
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 the tool has 0 parameters (normally a baseline of 4), the description implies a kilometer input ('Convert km to miles') while the input schema defines no properties. This creates a mismatch: an agent sees an empty schema but a description that suggests a parameter. The description fails to clarify that the tool takes no arguments or how the value 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 states a specific verb and resource: 'Convert km to miles.' It clearly indicates the conversion direction and is not a pure tautology, though it closely mirrors the tool name. It doesn't explicitly distinguish itself from sibling converters like x402-miles-to-km or x402-units-convert, so it doesn't earn 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?
There is no guidance on when to use this tool versus alternatives. The sibling list includes many overlapping converters (x402-units-convert, x402-miles-to-km, x402-metric-imperial), and the description gives no exclusions or context to help an agent choose this specific tool. The use case is only implicit in the name.
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.