x402-random-exponential
Random Exponential: Generate a random exponential number.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| n | No | N to process | |
| value | No | Value to process |
Random Exponential: Generate a random exponential number.
| 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?
No annotations are provided, so the description must carry the full behavioral burden. It only says 'Generate a random exponential number' and does not disclose whether a rate parameter is needed, whether outputs are continuous, whether results are deterministic, or what the response shape is. This is thin coverage for a generation 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 description is short and front-loaded, but the 'Random Exponential:' prefix is redundant with the tool name, and the rest repeats the same idea. It is minimal but not as tight as it could be because it wastes a few words restating the tool's name and function.
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 ambiguous parameters and no output schema, the description is insufficient. It does not explain what 'n' or 'value' mean, how they affect the generated number, whether one is a rate parameter, or what the return value looks like. An agent would struggle to call this tool correctly with only the provided information.
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?
Schema description coverage is 100%, so the baseline is 3 even without parameter details in the tool description. The schema's descriptions ('N to process', 'Value to process') are generic and somewhat unhelpful for a random exponential generator, but the tool description itself adds no parameter meaning, so it does not exceed the baseline.
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 uses a specific verb 'Generate' and identifies the resource as 'a random exponential number,' which is a concrete and meaningful statement of the tool's function. However, it does not explicitly distinguish itself from similar siblings like random-normal or random-range, so it is clear but lacks direct differentiation.
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 versus alternatives such as random-normal or random-range, and no mention of use cases, prerequisites, or exclusions. The description simply states what it does, leaving the agent to infer when it is appropriate.
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.