x402-sentence-count
Sentence Count: Sentence Count
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Sentence Count: Sentence Count
| 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, and it discloses nothing. It does not state whether the tool reads text from context, whether it is read-only, what output format it returns, or any limitations. The tool has zero input parameters and no output schema, making the description the only source of behavioral information, and it is empty.
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 short, but this is under-specification rather than effective brevity. The phrase 'Sentence Count: Sentence Count' contains only redundant words and fails to communicate any actionable information, so it does not earn its place.
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?
There is no output schema and no annotations, so the description is the only source of context. It fails to explain the tool's function, input source, return value, or any usage context. Even for a simple tool, this description is completely inadequate for an agent to decide to invoke it.
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, and schema description coverage is 100% because there is nothing to document. Per the rubric, 0 params gets a baseline of 4. However, the description still leaves ambiguity about where the text to count comes from, but this is not strictly a parameter semantics issue.
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 'Sentence Count: Sentence Count' is a pure tautology that simply restates the tool name. It does not say what the tool does with input, what kind of input it expects, or how it differs from the many sibling text tools like x402-avg-sentence-length, x402-sentence-split, or x402-word-count. An agent reading this cannot determine the tool's actual function.
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 whatsoever about when to use this tool versus alternatives. The description does not mention any conditions, prerequisites, or sibling tools that might be more appropriate for related tasks such as counting words, characters, or splitting sentences.
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.