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minia2a-mcp

x402-barcode

Barcode: Generate a barcode image URL from text via the tec-it renderer. Provide text plus optional format (default code128) and size; returns a PNG render URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNoSize to process
formatNoFormat to process

TDQS

C2.7/5.0
Behavior2/5

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

With no annotations, the description carries the full burden and only partially delivers. It usefully discloses the output type (PNG URL rather than binary data) and the default format (code128), but it omits that this relies on an external tec-it renderer with attendant network/rate-limit implications, says nothing about input constraints on the text, and no error behavior is described.

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 dense sentence that front-loads the action and efficiently packs renderer, inputs, default format, and return type. It is compact and readable, though its efficiency is slightly undermined by the misleading reference to a non-existent text parameter.

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?

With no output schema and no annotations, the description must compensate by explaining the return and constraints; it does state the PNG-URL return, which helps. But it omits accepted values/syntax for size and format, and the phantom text parameter is a fatal gap that makes the tool uncallable as documented.

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?

Although schema coverage is 100%, the schema descriptions ('Size to process', 'Format to process') are pure tautologies with no semantic content. The description adds a genuinely useful default (code128), but it instructs the agent to 'Provide text' while the schema has no text parameter at all — an agent following the description cannot correctly invoke this tool.

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 ('Generate'), a concrete resource ('barcode image URL'), and the rendering backend ('tec-it'), and even discloses the return form ('PNG render URL'). However, it does not distinguish itself from the sibling x402-barcode-generate, so an agent scanning the sibling list cannot tell which barcode tool to choose.

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 when-to-use guidance, no exclusion criteria, and no mention of alternatives. Given several closely related siblings (x402-barcode-generate, x402-qr-generate, x402-qr, x402-ean-validate), the agent is left to guess when this tool rather than another is appropriate. Usage context is only implied by the action described.

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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