x402-joules-to-calories
Joules To Calories: Convert joules to calories.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Joules To Calories: Convert joules to calories.
| 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 disclosing behavior, but it only says 'Convert joules to calories.' It does not disclose which calorie definition is used (e.g., thermochemical vs. food Calorie), rounding behavior, or return format. For a conversion tool where the calorie variant materially changes the result, this is too thin.
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 the action word 'Convert.' The 'Joules To Calories:' prefix is redundant with the tool name, but the overall size is appropriate and there is no rambling or irrelevant content.
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?
Despite the tool being simple, the description is incomplete for an agent that must invoke it correctly: there is no output schema, so the return value is not described; the input mechanism is unclear since the schema has no parameters; and the calorie type is unspecified. The description functions more as a label than as complete usage guidance.
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, which is the baseline-4 case; there are no parameter descriptions to contradict or supplement. The description does not explain how the value to convert is supplied, but that is arguably a schema-level gap rather than a parameter-semantics gap. No parameter semantics need to be added because no parameters exist.
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 states the operation: converting joules to calories, with a specific verb and resource. It distinguishes the direction from the sibling x402-calories-to-joules, though it does not explicitly name alternatives. The prefix 'Joules To Calories' largely repeats the tool name, but the core sentence is unambiguous.
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 similar converters such as x402-calories-to-joules or x402-units-convert. The context is only implied by the conversion phrase, with no explicit when-to-use or when-not-to-use guidance.
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.