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minia2a-mcp

x402-random-emoji

Random Emoji: Generate a random emoji.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nNoN to process
countNoCount to process

TDQS

C2.6/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description alone must disclose behavior, but it discloses only the bare action. It does not say whether count controls how many emojis are returned, whether n is accepted at all, what the output looks like, or whether anything about the response varies per call.

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

Conciseness3/5

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

At two short clauses, the text is certainly brief. But the leading 'Random Emoji:' label duplicates the tool name and the sentence that follows, wasting the opening position on redundancy rather than useful scoping detail.

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

Completeness2/5

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

For a tool with two defined parameters, no annotations, and no output schema, one sentence is not enough: parameter behavior, return format, and the relationship to x402-emoji are all left unspecified. The core action is communicated, but every consequential calling detail is missing.

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

Parameters2/5

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

Schema coverage is nominally 100%, but the property descriptions 'N to process' and 'Count to process' are generic boilerplate with no random-emoji-specific meaning, and the tool description adds nothing to clarify them. An agent cannot tell if count requests multiple emojis or what n represents, so the effective semantics are missing.

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

Purpose4/5

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

The phrase 'Generate a random emoji' states a clear verb and resource, so an agent knows exactly what the tool produces. However, the 'Random Emoji:' prefix simply restates the tool name, and nothing in the description separates this from the sibling x402-emoji or the many other x402-random-* tools.

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 about when to use this tool versus alternatives. With siblings including x402-emoji, x402-count-emoji, x402-remove-emoji, and a dozen x402-random-* generators, an agent has no basis for choosing between them.

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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