x402-is-ugly
Is Ugly: Check whether a number is ugly: positive with only 2, 3, and 5 as prime factors. Provide value.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Is Ugly: Check whether a number is ugly: positive with only 2, 3, and 5 as prime factors. Provide value.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It defines the mathematical concept but does not explain how input is conveyed given the empty schema, what the return value looks like (presumably a boolean), or how edge cases such as 1, 0, and negative numbers are handled. The dangling phrase 'Provide value' adds confusion instead of clarity.
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 text is short and the core definition is front-loaded, but the 'Is Ugly:' prefix redundantly echoes the tool name and 'Provide value.' is a dangling fragment that adds no useful information. Both could be removed without any loss.
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 predicate tool with no annotations, no output schema, and a non-obvious input mechanism, the description is incomplete. It explains what 'ugly' means but does not say how to invoke the tool, what result to expect, or how it differs from the sibling x402-is-ugly-number.
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 declares zero parameters, which would normally set a baseline of 4, but the description's 'Provide value' instructs the agent to supply input that the schema does not define. Instead of clarifying the calling convention, the description conflicts with the empty input schema, leaving the tool effectively uncallable as specified.
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 gives a specific operation ('Check whether') on a specific resource (a number) and precisely defines the predicate: positive with only 2, 3, and 5 as prime factors. However, it does not distinguish this tool from the near-identical sibling x402-is-ugly-number, so it misses the top score.
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 alternatives. This is a meaningful gap because the sibling list contains x402-is-ugly-number, which appears to perform the same check, leaving an agent with no way to choose between them.
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.