x402-cube-volume
Cube Volume: Volume of a cube.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Cube Volume: Volume of a cube.
| 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 full burden of behavioral disclosure, but it only states a truism. It does not mention units, output format, whether the tool is deterministic, how it obtains the cube side length, or any edge cases. The empty input schema is an additional red flag the description fails to address.
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 not genuinely concise: it spends both halves of 'Cube Volume: Volume of a cube' saying the same thing. Real conciseness would pack useful information into the limited space, but this is under-specification.
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?
This is a mathematical calculation tool with no annotations, no output schema, no parameters, and a circular description. An agent has no way to know what input to provide, what the return looks like, or how this differs from the many other volume tools. The definition is critically incomplete.
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 has 0 parameters and 100% coverage, so there are no parameter semantics the description needs to add. Baseline for 0 params is 4; the description neither helps nor hurts this dimension.
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 'Cube Volume: Volume of a cube' simply restates the tool name in natural language; it provides no verb, no formula, and no distinguishing features. Among many volume-related siblings (x402-volume, x402-box-volume, x402-sphere-volume), it does nothing to differentiate itself.
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 zero guidance on when to call this tool versus alternatives like x402-box-volume or generic x402-volume. No context, no exclusions, no mention of the fact that the input schema is empty and the side length must presumably be supplied somehow.
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.