x402-energy
Energy: Convert an energy value between joules, kilojoules, calories, kilocalories, watt-hours, kWh, BTU, and electronvolts. Provide value and from/to units.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Energy: Convert an energy value between joules, kilojoules, calories, kilocalories, watt-hours, kWh, BTU, and electronvolts. Provide value and from/to units.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the full behavioral disclosure burden. It correctly signals a pure, read-only conversion operation and lists supported units, which is useful. However, it says nothing about the return format, precision, handling of invalid or unknown unit spellings, or case-sensitivity, leaving some behavioral ambiguity.
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 single, front-loaded sentence with no redundant or promotional language. Every clause adds operational value: the domain label, the action, the supported unit list, and the required inputs.
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 an empty input schema and no output schema, the description does not fully equip an agent to invoke the tool correctly: it lacks exact parameter names, unit-string conventions, and any description of the response. It also fails to mention that specialized sibling converters exist, which is particularly relevant in such a large tool 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?
The input schema has zero parameters, so the description is effectively the only source of parameter semantics, and it does supply the key requirement: a numeric value and from/to units. It also enumerates the recognized units, which is genuinely useful, but it does not give exact parameter names, types, or the expected unit-string format, so it is not perfect.
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 uses a specific verb ('Convert') with a specific resource ('an energy value') and enumerates the supported units (joules, kilocalories, kWh, BTU, electronvols), which makes the purpose immediately clear. It does not explicitlly contrast itself with sibling tools like x402-units-convert or the one-pair converters, so it falls short of full sibling differentiation.
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 phrase 'Convert an energy value...' and 'Provide value and from/to units' implies when the tool should be used, but there is no explicit when-to-use/when-not-to-use guidance. It never names alternatives or explains why an agent should choose x402-energy instead of x402-calories-to-joules or x402-units-convert.
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.