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minia2a-mcp

x402-validator-suite

Validator Suite: Validate a value against eight formats in one call: email, URL, UUID, IP, credit card (Luhn), IBAN, ISBN and hex color.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputNoInput to process
valueNoValue to process

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations and no output schema, the description carries the full behavioral burden, but it does not explain what the tool returns (one boolean, per-format results, or a summary), how failures are reported, or edge-case behavior for empty/invalid inputs. It reveals only the surface-level validation action and format list.

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

Conciseness5/5

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

The description is a single efficient sentence that front-loads the purpose and lists all supported formats without unnecessary prose. Every element earns its place.

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?

The tool is simple enough that a short description could be complete, but two critical elements are missing: the return shape/behavior and any clarification of the dual input/value parameters. An agent has enough to guess the purpose but not enough to reliably invoke it correctly.

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?

The schema has 100% coverage, but both parameter descriptions are generic tautologies ('Input to process' and 'Value to process'). The tool description adds no guidance about which parameter to populate, whether both are accepted, or which takes precedence, and neither parameter is required. This ambiguity makes correct invocation uncertain.

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

Purpose5/5

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

The description names a specific action (validate), a clear resource (a value), and enumerates the eight exact formats supported. It is easily distinguishable from the many individual validator siblings because it explicitly advertises multi-format validation in one call.

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

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'In one call' implies this is the tool to use when multiple formats need checking at once, but the description never directly says when to prefer this over the individual validate-* tools. Usage context is implied rather than explicitly stated, and no exclusions or alternative routing are provided.

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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