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minia2a-mcp

x402-json-toml

JSON Toml: JSON Toml

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoData to process

TDQS

D1.3/5.0
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. It reveals nothing: no conversion direction, no expected input format, no error behavior, no output shape. This is a total absence of behavioral information.

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 short, but this is under-specification, not conciseness. A five-word tautology that repeats the tool name does not earn its place and provides no information an agent could act on.

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?

Even though the tool is simple (one parameter, no output schema), the description is completely inadequate. An agent cannot determine the conversion direction, the required input format, or how this relates to x402-toml-json, making correct invocation effectively impossible.

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 the parameter description 'Data to process' is generic and uninformative — it does not say whether the data should be a JSON string, a TOML string, or either. The tool description adds nothing beyond the schema, so even the baseline-3 credit for high schema coverage is not earned because the coverage is illusory.

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

Purpose1/5

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

The description 'JSON Toml: JSON Toml' is a pure tautology that restates the tool name without any verb or action. It does not state whether the tool converts JSON to TOML, TOML to JSON, or something else entirely, and it cannot be distinguished from the sibling x402-toml-json.

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. Given the sibling x402-toml-json exists, directionality could be disambiguated with a simple one-liner, but the description provides no context for selecting this tool over any of the other json-* or conversion siblings.

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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