x402-geometric-series-sum
Geometric Series Sum: Sum of geometric series.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Geometric Series Sum: Sum of geometric series.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not explain whether the sum is finite or infinite, how convergence is handled, what numeric precision is used, or what the return format is. The input schema is empty, leaving the actual calling contract completely 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 short and front-loads the topic, but it is under-specified rather than economically efficient. One sentence with no operational detail is minimalism without information value.
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 mathematical tool among hundreds of similar numeric tools, the description is severely incomplete. It fails to specify inputs, output type, finite vs. infinite series, convergence conditions, or how it differs from x402-infinite-geometric-sum and x402-geometric-series. An agent cannot reliably invoke this tool based on the provided definition.
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 defines 0 parameters and has 100% coverage, meaning there are no parameters to document. The description therefore does not need to explain parameter semantics. However, the presence of 0 parameters raises a question about how the tool receives its inputs, which the description does not address.
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 'Geometric Series Sum: Sum of geometric series.' is a near-tautology that merely restates the tool name without specifying what inputs are accepted, what output is produced, or how it differs from closely related siblings like x402-geometric-series, x402-arithmetic-series-sum, or x402-infinite-geometric-sum.
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. With similar tools like x402-geometric-series, x402-geometric-mean, x402-geometric-pmf, and x402-infinite-geometric-sum in the sibling list, an agent has no basis for choosing this tool.
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.