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minia2a-mcp

x402-remove-first-word

Remove First Word: Remove First Word

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

C2/5.0
Behavior1/5

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 fails completely. It does not state what the input source is, whether the operation mutates state or returns a transformed string, what the output format is, or any side effects. The empty input schema further deepens the mystery, and the description offers no insight into how the tool can be invoked meaningfully.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely short but is under-specified rather than concise. It repeats the tool name twice and contains no informational content that would help an agent invoke it. It is not that every sentence earns its place; it is that the only sentence is worthless.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This description is completely inadequate for a tool with no annotations, no output schema, and no parameters. The agent has no idea what string is operated on, how input is provided, what the result looks like, or how this tool fits with the hundreds of siblings. For any tool that actually removes a word, this level of ambiguity is disqualifying.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the baseline is 4. The description does not add parameter meaning, but there are no parameters to describe. However, it also fails to explain where the text being processed comes from, which is a gap in overall context, but not specifically in parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Remove First Word: Remove First Word' is a pure tautology that simply restates the tool name without adding any clarifying detail. It says what the name already says, but gives no specifics about what resource it acts on or what the operation entails. It does not distinguish itself from string manipulation siblings beyond the name itself.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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, what input it expects, or how it relates to alternatives like x402-remove-last-word or x402-remove-accents. The description provides no context for tool selection, leaving the agent without a basis for choosing it over similarly named tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

D1.6/5.0
Disambiguation1/5

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.

Naming Consistency2/5

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.

Tool Count1/5

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.

Completeness2/5

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.

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