x402-truncate-words
Truncate Words: Truncate words.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Truncate Words: Truncate words.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations to carry the behavioral burden, and the description discloses nothing about how the tool behaves beyond the word 'truncate'. It does not state defaults, side effects, output format, or constraints, so an agent cannot anticipate the tool's 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 tiny but not meaningfully concise: 'Truncate Words:' and 'Truncate words' are redundant. It is under-specified rather than efficiently informative, 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?
With no annotations, no input schema properties, and no output schema, the description leaves every meaningful detail unstated. An agent has no way to know what input to provide, what 'truncate' entails, or what result to expect. This is completely inadequate for selecting and invoking the tool correctly.
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 the baseline per the rubric is 4. There is no parameter information to explain, and the description does not mislead about parameters. The lack of any input mechanism is more a contextual completeness problem than a parameter semantics one.
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 "Truncate Words: Truncate words". restates the tool name rather than explaining what truncation means, what input is affected, or what output is produced. It provides a verb and a resource, but it is essentially tautological and does not distinguish this tool from x402-truncate, x402-truncate-middle, or x402-truncate-decimal.
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 gives no guidance on when to use this tool versus any of the dozens of sibling text tools. It does not mention alternatives, prerequisites, or context in which truncation is appropriate.
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.