x402-remove-last-word
Remove Last Word: Remove Last Word
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Remove Last Word: Remove Last 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 discloses nothing. It fails to explain edge-case behavior such as handling of empty strings, trailing punctuation, whitespace-only input, or how the input is even received given the empty parameter schema.
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 short, but this is under-specification rather than conciseness. A single sentence that repeats the tool name earns no structural credit; there is no front-loaded useful information at all.
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?
Given no annotations, no output schema, an empty input schema, and a text-manipulation use case, the description is completely inadequate. An agent cannot determine the input mechanism, the definition of 'word', the return value, or how this differs from x402-remove-first-word and other string-removal siblings.
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 schema has zero parameters, which is itself anomalous for a text-transformation tool — an agent cannot determine how the text to process is supplied. Schema coverage is 100% only vacuously. The tautological description does nothing to clarify how input is passed or what the single implicit input (a string?) requires.
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 'Remove Last Word: Remove Last Word' is a pure tautology that merely restates the tool name. It conveys no information beyond what the name already provides and does not specify what counts as a word, what input form it expects, or what output it produces.
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 zero guidance on when to use this tool versus alternatives. With dozens of related text-manipulation siblings (x402-remove-first-word, x402-remove-whitespace, x402-remove-accents, x402-remove-punct), the description offers no distinguishing context or exclusions.
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.