x402-bmi
BMI: Calculate Body Mass Index.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| height | No | Height to process | |
| weight | No | Weight to process |
BMI: Calculate Body Mass Index.
| Name | Required | Description | Default |
|---|---|---|---|
| height | No | Height to process | |
| weight | No | Weight to process |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden of behavioral disclosure. It only says 'Calculate Body Mass Index' and does not explain input units, whether height or weight are optional, edge cases, error behavior, or expected output. This is a meaningful gap for a calculation that depends on unit consistency (e.g., kg/m^2 vs lbs/in^2).
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 extremely concise and front-loaded: 'BMI: Calculate Body Mass Index.' It has no wasted words. It is appropriately short for a simple calculator, though it borders on under-specification rather than disciplined brevity.
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 tool with no annotations and no output schema, the description is too thin. An agent cannot reliably know what units to use, whether both parameters are required, or what result format to expect. These are essential details for correctly invoking a BMI calculation.
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?
Schema description coverage is 100%, so the baseline is 3 even though the main description adds no parameter-level detail. However, the schema descriptions ('Height to process', 'Weight to process') are essentially tautological and provide no unit or format information, so the description does little to help an agent supply correct parameter values.
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 action ('Calculate') and a specific resource ('Body Mass Index'), making the tool's core purpose clear. It is somewhat redundant with the tool name x402-bmi, but it does add the verb and distinguishes this from the many other x402-* calculators in the sibling list.
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 implies 'use this when you need BMI,' which is a reasonable contextual cue given the tool name and siblings. However, it provides no explicit guidance about when not to use it, alternative tools, or any prerequisites like required units or measurements.
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.