x402-fibonacci
Fibonacci: Fibonacci numbers.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| n | No | N to process | |
| count | No | Count to process | |
| index | No | Index to process | |
| sequence | No | Sequence to process |
Fibonacci: Fibonacci numbers.
| Name | Required | Description | Default |
|---|---|---|---|
| n | No | N to process | |
| count | No | Count to process | |
| index | No | Index to process | |
| sequence | No | Sequence to process |
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 reveals nothing about computation type, input constraints, output format, side effects, or failure modes. An agent cannot anticipate what will happen when invoking this 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 a four-word phrase, which is so short it conveys almost nothing. This is under-specification rather than effective conciseness. A brief description can score high only when every word carries useful meaning; her, the only information is a restatement of the resource name.
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?
With no output schema, no annotations, and only a tautological description, the definition is completely inadequate for a tool with four parameters. An agent cannot determine which parameter to supply, what the tool returns, or how it relates to the four other Fibonacci tools in the sibling list.
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. The schema descriptions are generic ('N to process', 'Count to process', 'Index to process', 'Sequence to process') and the tool description adds no meaning beyond them. Since every parameter has a description in the schema, the baseline applies.
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 'Fibonacci: Fibonacci numbers.' restates the tool name without stating a verb or operation. It does notindicate whether this tool computes, generates, checks, or indexes Fibonacci numbers, and it gives no way to distinguish this tool from siblings like x402-fibonacci-n, x402-fibonacci-series, x402-fibonacci-index, or x402-fibonacci-retracement. This is essentially a tautology.
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 instead of the multiple Fibonacci-related siblings. No context, no exclusions, no examples, and no routing signal. An agent has no basis for deciding between x402-fibonacci and x402-fibonacci-n, x402-fibonacci-index, or x402-fibonacci-series.
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.