x402-avg-word-length
Avg Word Length: Length of avg word.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Avg Word Length: Length of avg word.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure, and it fails to do so. It does not explain what input the tool expects, what counts as a word, whether punctuation is handled, what format the result takes, or any edge-case behavior.
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, which is appropriate for a simple utility, but it wastes its tiny budget by repeating the tool name: 'Avg Word Length' and 'Length of avg word' say essentially the same thing. It is compact yet redundant and fails to use the space to add new information.
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?
With no annotations, no output schema, and an empty input schema, the description is the only information an agent has, and it is almost entirely uninformative. It does not state what text source is analyzed, how the tool is invoked, what is returned, or how it differs from the many related text-analysis tools.
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 there is no parameter documentation burden for the description to carry. Per baseline, a no-parameter tool does not need parameter-level explanations, and no parameter information is missing.
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 is essentially a tautology: 'Avg Word Length: Length of avg word.' restates the tool name without adding a clear verb-action statement or resource definition. It does not distinguish this tool from closely related siblings like x402-avg-sentence-length or x402-word-count.
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 on when to use this tool versus alternatives. An agent cannot tell whether to call x402-avg-word-length, x402-avg-sentence-length, x402-char-count, or x402-word-count based on the description alone.
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.