x402-collatz
Collatz: Generate the Collatz sequence for a positive integer n. Provide n; returns the sequence until it reaches 1.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Collatz: Generate the Collatz sequence for a positive integer n. Provide n; returns the sequence until it reaches 1.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It does state the core return behavior (sequence terminates at 1), but it misleadingly instructs 'Provide n' while the input schema defines zero parameters, leaving the agent unable to pass the required input. Edge cases such as n=1, n=0, negative inputs, or very large n are not addressed.
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 two short sentences with the operation front-loaded and no filler. There is minor redundancy between 'for a positive integer n' in the first sentence and 'Provide n' in the second, but overall the structure is efficient.
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 minimal tool with no annotations, no output schema, and an empty input schema, the description is the sole source of guidance and it is incomplete. It omits how the required n is actually supplied, does not define behavior for boundary inputs, and fails to distinguish itself from the sibling x402-collatz-sequence. An agent would struggle to invoke this correctly.
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 0 parameters normally warrants a baseline of 4, the description explicitly tells the agent to 'Provide n' while the schema declares an empty properties object. This is an active contradiction between the description and the schema: the agent is told an input is required but is given no parameter definition through which to supply it. This is actively misleading rather than merely unhelpful.
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 verb and resource: 'Generate the Collatz sequence for a positive integer n' and specifies the return condition ('returns the sequence until it reaches 1'). This is clear and actionable. However, it does not differentiate from the near-identical sibling x402-collatz-sequence, so an agent cannot tell which of the two to use.
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?
The description gives no guidance on when to use this tool versus x402-collatz-sequence, x402-hailstone-length, or x402-hailstone-max, all of which operate on the same mathematical concept. It only implies usage ('Provide n') without any exclusions, prerequisites, or alternative routing.
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.