x402-is-armstrong-number
Is Armstrong Number: Is Armstrong Number
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Is Armstrong Number: Is Armstrong Number
| 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, and it discloses nothing: no return type, no error behavior, and no indication of how the number being tested is supplied. The empty input schema makes this omission critical, leaving the agent without any information about how to invoke the tool.
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 tiny but this is under-specification, not conciseness: it repeats the same phrase twice and contains zero informational content. There is nothing front-loaded because there is nothing useful to load.
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 schema, absent annotations, and no output schema, the description needed to explain the definition/scope of 'Armstrong number', the input mechanism, and the return value. It explains none of these, and with overlapping siblings (x402-is-narcissistic, x402-is-narcissistic-number) available, an agent has no way to use this tool correctly.
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 zero parameters, so the 0-parameter baseline reduces the documentation burden. However, the tool's purpose requires a numeric subject, and neither schema nor description explains how that number is provided, so the agent cannot construct a correct call. The description adds no meaning beyond the empty schema.
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 'Is Armstrong Number: Is Armstrong Number' is a pure tautology that merely restates the tool name. It gives no definition of an Armstrong number, no verb+resource statement, and no way to distinguish this tool from near-identical siblings such as x402-is-armstrong and x402-is-narcissistic-number.
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 no guidance on when to use this tool. The sibling list contains multiple overlapping predicates (x402-is-armstrong, x402-is-narcissistic, x402-is-narcissistic-number), and the description offers no selection criteria or mention of any alternative, so an agent cannot route 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.