x402-length
Length: Convert a length value between millimeters, centimeters, meters, kilometers, inches, feet, yards, and miles. Provide value and from/to units.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Length: Convert a length value between millimeters, centimeters, meters, kilometers, inches, feet, yards, and miles. 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 provided, the description carries the full burden of explaining behavior. It does communicate the supported unit set and the need for value and from/to units. However, it does not describe output format, precision, rounding behavior, or how invalid units or values are handled. For a pure conversion tool, this is adequate but not fully transparent.
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 compact sentence that front-loads the tool's purpose and then states the required inputs. Every phrase earns its place, with no filler or repetition. It is appropriately sized for the simplicity of the operation.
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 simple length-conversion tool, the description covers the supported units and the essential input requirements. The lack of an output schema and annotations is mitigated by the inherent simplicity of the operation. It could be more complete by specifying the result format, but nothing critical is missing for an agent to understand the tool's basic purpose.
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 the description is the only source of parameter meaning. It usefully identifies the required inputs (value and from/to units) and lists the valid unit options. It falls short of formal parameter names or types, but with a 0-parameter schema the description provides strong compensating guidance.
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 tool's function: converting a length value between a specific set of units. The verb 'Convert' and resource 'length value' are concrete, and the enumerated units make the scope unambiguous. However, it does not explicitly distinguish itself from sibling conversion tools like x402-cm-to-inches or x402-units-convert.
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 instruction 'Provide value and from/to units' gives clear guidance on what the agent must supply when invoking the tool. It does not explicitly state when to choose this tool over the many sibling conversion tools, but the context of generic length conversion is clear and no exclusions are offered.
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.