x402-random-quote
Random Quote: Generate a random quote.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| n | No | N to process | |
| value | No | Value to process |
Random Quote: Generate a random quote.
| Name | Required | Description | Default |
|---|---|---|---|
| n | No | N to process | |
| value | No | Value to process |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations and no output schema, the description must disclose behavior on its own, but it only says quotes are generated randomly. It does not mention what the optional 'n' and 'value' parameters do, whether any side effects occur, or what response shape to expect, leaving the behavior largely opaque.
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 extremely short and front-loaded, containing no wasted words. The 'Random Quote:' prefix is somewhat redundant with the following phrase, but overall it is an appropriately sized summary for a simple tool.
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 tool with two unexplained optional parameters and a large set of overlapping siblings, the description is too thin. It lacks parameter semantics, output information, and guidance on how this differs from related random-content tools, so an agent cannot invoke it with confidence.
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?
Although schema coverage is 100%, the parameter descriptions are generic boilerplate ('N to process' and 'Value to process') that add no real meaning about how to use them. The tool description also does not explain how 'n' or 'value' influence the random quote, so the agent cannot construct a meaningful call.
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 action ('Generate') and resource ('a random quote'), making the tool's purpose clear at a glance. However, it does not differentiate from sibling quote-like tools such as x402-kanye-quote or x402-advice-slip, so it only partially separates 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 no guidance about when to use this tool over alternatives like x402-random-joke, x402-random-fact, or x402-kanye-quote. No context, exclusions, or conditions are given, leaving an agent to guess which random-content tool fits the user's request.
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.