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minia2a-mcp

x402-vector-dot

Vector Dot: Vector Dot

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
aNoA to process
bNoB to process
v1NoV1 to process
v2NoV2 to process

TDQS

D1.5/5.0
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, and it discloses nothing: no mention that this is a pure computation, no input-format expectations, no edge cases, no return behavior. The text is entirely restatement.

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 definition is short, but this is under-specification rather than conciseness — the single sentence merely restates the name. Per calibration, a one-phrase tautology does not earn credit for being concise.

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 no annotations, no output schema, four opaque string parameters, and a tautological description, an agent cannot determine which inputs to populate, how vectors are formatted, or what result to expect. The four-parameter shape for a binary operation (a, b, v1, v2) is especially ambiguous and the description leaves it completely unresolved.

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?

Schema coverage is nominally 100%, but each parameter description ('A to process', 'B to process', etc.) is a content-free placeholder that fails to explain what the parameter represents, how a vector should be encoded as a string, or which parameters pair together (a·b vs v1·v2). The tool description adds nothing to compensate for this semantic void.

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 'Vector Dot: Vector Dot' is a pure tautology — it restates the tool name in both halves and adds zero information. It never states that this computes the dot product of two vectors, how inputs are represented, or how it differs from siblings like x402-vector-cross and x402-vector-norm.

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 at all on when to use this tool versus related mathematical siblings (x402-vector-cross, x402-vector-norm, x402-cosine-similarity). The description is not misleading, but it provides no decision support for tool selection.

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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