x402-meters-to-feet
Meters To Feet: Convert meters to feet.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Meters To Feet: Convert meters to feet.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the full burden of behavioral disclosure, and it fails critically: the input schema has zero parameters, yet the description never explains how the meters value is supplied to the tool. It also discloses nothing about rounding/precision behavior, handling of invalid input, or return format. The only disclosed trait is the trivial fact that a conversion occurs.
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 brief and front-loaded, with no fluff or excess sentences. However, the 'Meters To Feet:' prefix is redundant with the tool name, and the extreme brevity is achieved at the cost of omitting operationally critical details such as how input is passed and what output precision is expected.
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 an agent to invoke this tool correctly, it must know how to provide the meters value, but the empty input schema offers no parameters and the description offers no explanation. With no output schema and no annotations either, the invocation contract is entirely unspecified. Even for a trivial conversion tool, the description should at minimum clarify how the value reaches the function and what the result looks like.
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 schema contains no parameters, so the baseline is 4. The description correctly conveys that the tool's semantic domain is the meters-to-feet conversion, which is the only parameter-level meaning an agent needs given the empty schema. It does not, however, resolve the apparent contradiction of a conversion tool whose schema accepts no input.
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 meters to feet'), making the operation unambiguous. The directionality meters→feet distinguishes it from the sibling x402-feet-to-meters and other unit converters. It loses a point because the lead-in 'Meters To Feet' merely restates the tool name and the description adds nothing beyond the bare operation.
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 on when to use this tool versus the many alternatives in the sibling list such as x402-units-convert, x402-metric-imperial, x402-meters-to-yards, or x402-feet-to-meters. There is no mention of precision, rounding expectations, or which scenarios favor this dedicated converter over a general-purpose one. An agent must infer all selection context from the name alone.
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.