x402-gb-to-mb
Gb To Mb: Convert gb to mb.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Gb To Mb: Convert gb to mb.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral transparency burden, but it only says 'Convert gb to mb.' It does not disclose the conversion factor (decimal vs binary), how the value is supplied, or what the output looks like, leaving important behavior 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 extremely short and front-loaded with the conversion direction. The leading 'Gb To Mb:' is redundant with 'Convert gb to mb,' so there is minor waste, but overall every essential piece of the intended operation is present.
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 no-parameter tool with no output schema, the description should explain how the conversion input is handled and what result is returned; it does neither. An agent seeing an empty input schema cannot determine how to request a specific value (e.g., 5 GB), so the definition is incomplete for correct invocation.
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?
The input schema has zero parameters, so there is no parameter-level detail for the description to add; per the zero-parameter baseline, the simple unit-direction statement is sufficient at the schema level. It does not resolve how an input value would be provided, but that is a contextual gap rather than a parameter-documentation gap.
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 the operation explicitly: 'Convert gb to mb' with a clear verb and resource pair. It identifies the conversion direction, enough to distinguish it from the opposite x402-mb-to-gb, but it does not go beyond restating 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?
Usage is implied by the conversion direction: call this when you need a gigabyte-to-megabyte conversion. There is no explicit when/when-not guidance, no mention of alternatives like x402-data-size or x402-units-convert, and no exclusions.
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.