x402-math
Math: Safe math expressions. ๐ 5 free trial calls per registered wallet
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | Q to process | |
| expr | No | Expr to process | |
| expression | No | Expression to process |
Math: Safe math expressions. ๐ 5 free trial calls per registered wallet
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | Q to process | |
| expr | No | Expr to process | |
| expression | No | Expression to process |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden. It does disclose that the tool is 'safe' and that calls are metered with '5 free trial calls per registered wallet', hinting at wallet registration and usage limits. However, it does not define what 'safe' permits or excludes, and it says nothing about result format, error behavior, or whether side effects exist.
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 very short and front-loads the core subject before the free-trial note. It contains little fluff, though the 'Math:' prefix is somewhat redundant with the tool name. The brevity is a strength here, but it leaves important information unstated.
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 no annotations, no output schema, and three optional-looking parameters, the description is under-specified. It does not explain expression syntax, the relationship between q, expr, and expression, what the response looks like, or when calling with no parameters would be invalid. An agent can guess but cannot call the tool with full 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?
Schema description coverage is 100%, so the baseline is 3 even though the tool description adds no parameter-level detail. The schema descriptions like 'Q to process' and 'Expr to process' are largely tautological, and the description does not clarify whether q, expr, and expression are aliases or which one an agent should prefer.
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 'Math: Safe math expressions' identifies the resource domain and a safety property, but it lacks an explicit verb such as 'evaluate', 'calculate', or 'compute'. It is not a pure tautology, but it is vague about the actual operation and does not differentiate this tool from the many sibling math/calculation tools.
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 versus alternatives, no exclusions, and no mention of which sibling tools would be more appropriate for related math tasks. The free-trial sentence is metering context rather than usage guidance, so an agent gets no help making a selection decision.
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.