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ANIME INTELLIGENCE / AI PURCHASE INTELLIGENCE

Merchant Offer Search

merchant_offer_search
Read-onlyIdempotent

Search exact-MPN offers from merchants that publish machine-readable inventory, fulfillment and trust evidence. Ranking is evidence-based and not pay-to-rank.

Input Schema

NameRequiredDescriptionDefault
limitNo
part_numberYes
manufacturerNo
buyer_countryNoJP

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.2/5.0
Behavior4/5

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

Annotations already declare readOnly/openWorld/idempotent/non-destructive, so safety is covered. The description adds two genuinely non-obvious traits beyond that: results are limited to merchants publishing machine-readable evidence (so a thin result set is an expected outcome, not a failure) and ranking is evidence-based rather than pay-to-rank, which tells the agent the ordering is trustworthy. Pagination and result-volume behavior are not disclosed, keeping it short of a 5.

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 sentences, front-loaded with what is searched and scoped by the merchant-evidence constraint. The second sentence earns its place by disclosing ranking policy, though the 'not pay-to-rank' phrasing leans slightly promotional.

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 not be explained, and annotations carry the safety profile. What is missing is the operational context an agent needs to call it well: guidance on exact-MPN availability versus fuzzy search, what buyer_country changes, and how limit interacts with ranking.

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% across four parameters. The description only transmits that part_number is an exact MPN; it says nothing about manufacturer, buyer_country (default 'JP' — a significant default an agent should know about), or limit (default 20). The description does not compensate for the near-total lack of structured parameter documentation.

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?

States a specific verb and resource ('Search exact-MPN offers from merchants') and narrows the resource to merchants that publish machine-readable inventory, fulfillment and trust data. That is more precise than the sibling names (commerce_search, parts_search) would suggest, though it never explicitly contrasts itself with those siblings, so an agent still has to infer the boundary.

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 statement of when to use this versus commerce_search, parts_search, best_place or landed_cost, and no exclusions. The only implicit guidance is the word 'exact-MPN', which hints the part_number must be an exact manufacturer part number rather than a fuzzy query.

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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