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ANIME INTELLIGENCE / AI PURCHASE INTELLIGENCE

Large-Market Commerce Search

commerce_search
Read-only

Search consumer electronics, automotive parts, enterprise procurement, MRO and electronic components. Automotive/B2B recommendations require exact OE/MPN/part identity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
mpnNo
limitNo
queryYes
domainYes
oe_numberNo
part_numberNo
manufacturer_part_numberNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint=false and destructiveHint=false, so the safety profile is covered. The description adds only the input-identity constraint for automotive/B2B; it does not disclose result behavior, cross-domain ranking, or that identity-based lookups differ from keyword queries.

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?

Two tight sentences with zero filler, and the domain coverage is front-loaded ahead of the identity caveat. Efficient, though it is arguably too short given the 7-parameter surface it governs.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need no explanation, and annotations cover safety. However, with 7 parameters at 0% schema coverage and no sibling routing, the definition is thin for the tool's complexity and leaves key selection ambiguity 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 description coverage is 0%, so the description carries the full burden, yet it only gestures at 'OE/MPN/part identity.' It never explains the distinction among the three identity params (mpn, part_number, manufacturer_part_number), when to use each, or what 'limit' controls.

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 ('Search') and enumerates the resource domains (consumer electronics, automotive parts, enterprise procurement, MRO, electronic components), which map onto the domain enum. It is clear what the tool does, though it names no sibling to distinguish itself from the many adjacent shopping/intelligence tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

One conditional requirement is given: 'Automotive/B2B recommendations require exact OE/MPN/part identity.' This implies how to use the tool for those domains but offers no explicit when-to-use vs alternatives guidance and never routes the agent away from or toward any sibling.

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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