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minia2a-mcp

x402-ua-parser

Ua Parser: Parse a User-Agent string — browser, OS, device.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
uaNoUa to process
useragentNoUseragent to process

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries full responsibility for behavioral disclosure, and it provides almost none. It reveals the parsing categories (browser, OS, device) but says nothing about failure behavior on malformed input, output format, or edge cases. For a tool with zero annotation coverage, this is a meaningful gap, though it is not misleading.

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

Conciseness4/5

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

The description is a single sentence with the core purpose front-loaded before the output details. The 'Ua Parser:' prefix is redundant with the tool name and wastes a few words, but otherwise every phrase earns its place. It is compact without being vacuous.

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 parse operation with no output schema, no annotations, and two seemingly synonymous parameters, the description is incomplete. An agent cannot determine the expected return shape, how to choose between 'ua' and 'useragent', or what happens on an unparseable string. The near-duplicate sibling x402-ua-parse also goes unaddressed, leaving the agent without enough context to invoke this tool confidently.

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% — both 'ua' and 'useragent' have descriptions ('Ua to process', 'Useragent to process'), so the baseline is 3. The description itself adds no parameter-level meaning and, more importantly, does not clarify whether the two parameters are aliases of each other, which one takes precedence, or whether both are required. The schema's terse descriptions leave this ambiguity unresolved.

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 description states a specific verb ('Parse'), a specific resource ('User-Agent string'), and the outputs produced ('browser, OS, device'). This is functional and informative. However, it does not differentiate from the near-identical sibling x402-ua-parse, and the 'Ua Parser:' prefix partially restates the tool name, so it falls short of a 5.

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?

The description offers no guidance on when to use this tool versus alternatives. This is especially problematic given the sibling list contains x402-ua-parse, which appears to be a duplicate or near-duplicate, and the description never explains the difference or which to prefer. There is no when-to-use, when-not-to-use, or alternative routing.

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.

Resources