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minia2a-mcp

x402-color

Color: Color utilities — convert, blend, and manipulate colors.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bNoB to process
gNoG to process
rNoR to process
colorNoColor to process

TDQS

C2.4/5.0
Behavior2/5

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 neither the return format nor the acceptable input shapes (e.g., hex strings, 0-255 RGB components), nor whether operations are pure transformations. The phrase 'convert, blend, manipulate' only lists categories of behavior without specifying what the tool actually does in a single call.

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

Conciseness3/5

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

The description is short and front-loaded with no filler, which is good, but it is terse to the point of being uninformative. A measurement of conciseness must weigh that the little text present does not carry enough information to justify its length — it is minimally adequate, not earnestly complete.

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?

Given four parameters, no output schema, no annotations, and a sprawling sibling set with many color-specific tools, this description is substantially incomplete. It does not state the operation semantics or expected parameter usage, leaving the agent unable to correctly select and invoke the tool with confidence.

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%, every parameter description is the tautological placeholder '<X> to process' and adds no real meaning. The core description does not explain what r, g, b, and color represent, what formats they take, or how they relate to conversion/blending/manipulation. Beyond the property names hinting at RGB, the agent has no semantic grounding for constructing a valid call.

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

Purpose3/5

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

The description names a resource (colors) and verbs (convert, blend, manipulate), so it is not a tautology. However, the scope is too broad and it does not distinguish this tool from its many dedicated siblings (x402-color-converter, x402-color-blend, x402-color-shade, x402-rgb-to-hex, x402-hex-to-rgb, etc.). An agent cannot tell what specific operation this tool performs or why it exists alongside those siblings.

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 guidance about when to use this tool versus the dedicated color siblings. The description does not state which parameter combinations correspond to which operations (convert vs. blend vs. manipulate), and it offers no examples or exclusions. The agent is left to guess which tool fulfills a given color task.

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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