x402-ounces-to-grams
Ounces To Grams: Convert ounces to grams.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Ounces To Grams: Convert ounces to grams.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the full burden of explaining behavior. It only states the conversion operation and omits essential behavioral facts: how the ounces amount is supplied (schema has zero parameters), what the output looks like, and whether any precision or rounding rules apply.
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 'Ounces To Grams' and 'Converst ounces to grams' are redundant, so the second phrase earns little of its place. It is under-specified rather than efficiently compact.
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?
Given an empty input schema, no output schema, and no annotations, the description should clarify the no-argument calling convention or the return format. It does neither, so an agent cannot reliably predict what happens when the tool is invoked.
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 declares zero parameters (coverage 100%), so the baseline is 4, but the description does not explain how a caller communicates the value to be converted. Naming the units ounces and grams is helpful, yet the empty schema plus terse description leaves the invocation contract ambiguous.
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?
"Convert ounces to grams" names a specific source and target unit and is distinguishable from the sibling x402-grams-to-ounces by direction. However, it mostly restates the tool name and provides no finer detail about what the conversion yields, so it stops short of 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?
The description lacks any explicit guidance on when to prefer this tool over alternatives like x402-grams-to-ounces or x402-units-convert. The only hint is the conversion direction, which implies use when ounces need to become grams, but no exclusion or alternative is named.
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.