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minia2a-mcp

x402-percent

Percent: Percentage calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
totalNoTotal to process
valueNoValue to process
percentNoPercent to process

TDQS

D1.7/5.0
Behavior1/5

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: no output format, no operation semantics, no explanation that all three parameters are optional, and no precision/rounding behavior. The schema itself signals 0 required parameters, which makes the absence of any behavioral explanation especially damaging.

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 brief, but this is under-specification rather than conciseness. A single three-word definition that fails to distinguish the tool from siblings does not earn its place; it conveys almost no information.

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?

For a tool with an ambiguous operation, three optional string parameters, no output schema, and a huge space of overlapping percent/percentage siblings, the description is drastically incomplete. An agent cannot determine what calculation is performed, what inputs are required, what it returns, or how it differs from the sibling tools.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline is 3 even though the tool description adds no parameter-level meaning. However, the schema descriptions ('Total to process', 'Value to process', 'Percent to process') are themselves tautological and give no operational semantics, so the description does nothing to help an agent know which parameters to supply for which calculation.

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 'Percent: Percentage calculators.' essentially restates the tool name ('Percent') and provides only a category label rather than a specific function. It does not state what operation is performed, which is critical given the dozens of percent-related siblings (x402-percentage-change, x402-percent-of, x402-percent-to-ratio, x402-increase-by-percent, etc.). This is close to a tautology.

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

Usage Guidelines1/5

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. The sibling list contains many overlapping percentage tools, and the description names none of them, states no exclusion criteria, and gives no context that would let an agent choose 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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