x402-add-days
Add Days: Add days to a date.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Add Days: Add days to a date.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It simply states 'Add days to a date' but does not explain how the date is provided, whether the operation mutates input or returns a new value, how calendar edge cases like month/year overflow are handled, or what the output format is. The agent has no way to predict the tool's behavior beyond the bare operation.
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-loaded, with no extraneous detail. The 'Add Days:' prefix is somewhat redundant with the tool name, but the overall body is efficiently sized. It earns a high score for conciseness, though the brevity comes at the cost of useful context.
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?
Given the empty schema, lack of annotations, and lack of an output schema, the description needed to explain how inputs and outputs are conveyed; it does not. With siblings like x402-add-business-days and x402-add-years, the definition leaves critical ambiguity about date formats, parameter sourcing, and return behavior. The tool is not adequately specified for an agent to call it confidently.
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 input schema has zero properties, so there are no parameters to describe. Per the rubric baseline for 0 parameters, the description is not penalized for missing parameter-level detail. Still, the description's mention of 'days' and 'date' hints at the core concepts the tool operates on, even though the schema offers no structured way to pass them.
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 clearly identifies the operation: adding days to a date. It uses a specific verb and resource, which is enough for a basic understanding. However, it does not differentiate itself from closely related siblings like x402-add-business-days, x402-add-hours, or x402-add-months, so an agent could not reliably distinguish it without additional context.
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. The description does not mention exclusions, prerequisites, or any conditions under which an agent should choose this tool over the many sibling date-manipulation tools. The agent is left to infer usage solely from the tool's name.
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.