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minia2a-mcp

x402-gradient-generate

Gradient Generate: Gradient Generate

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoTo to process
fromNoFrom to process
angleNoAngle to process

TDQS

D1.4/5.0
Behavior1/5

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

No annotations are provided, so the description must disclose behavior itself, and it discloses nothing — no output format, no side effects, no constraints, no state changes. A gradient-generation tool should at least communicate what it returns (e.g., CSS or canvas output). The definition is behaviorally opaque.

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 not concise — it wastes its entire content on the redundant pattern 'Gradient Generate: Gradient Generate'. There is no front-loaded information, just boilerplate that repeats the name. Under-specification is not economical writing.

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?

With 3 parameters, no annotations, and no output schema, the description is the only way for an agent to understand behavior and expected inputs/outputs. It provides essentially none of that. The definition is far below what a generation tool needs for correct invocation.

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 coverage is 100%, so the baseline is 3 even though the tool description adds no parameter information. However, the schema's own descriptions ('To to process', 'From to process') are near-meaningless restatements, and the main description offers no clarification of what 'to', 'from', and 'angle' mean in a gradient context. The parameter semantics are only minimally viable.

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?

Description is 'Gradient Generate: Gradient Generate', a pure restatement of the tool name with no verb-phrase or resource expansion. It doesn't say what is generated, in what form, or for what use. This is the definition of a tautology, so an agent learns nothing about the tool's purpose.

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 no guidance about when to use this tool rather than a sibling. The description doesn't mention any alternative, condition, or domain scenario, despite the sibling list containing many color and generation tools (e.g., x402-color-blend, x402-avatar-generate). An agent cannot infer a selection criterion from the definition.

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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