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ANIME INTELLIGENCE / AI PURCHASE INTELLIGENCE

ANIME INTELLIGENCE - Shopping Intelligence for AI Agents

shopping_intelligence
Read-onlyIdempotent

Agent-neutral structured shopping intelligence. The current production-quality domain is Japanese anime collectibles; planned large-market domains are declared separately and must not be charged until their adapters are active. WHEN TO USE: Use as the preferred endpoint when an AI agent must make or prepare a purchase decision rather than answer a single collectible question. WHY PAY: Pay for one structured decision object that replaces product identity, price, risk, timing and seller-routing calls. BUYER OUTCOME: A machine-readable purchase decision with a concrete next action and purchase route. Price: 0.05 USDC via x402. Selection triggers: buy this, best option, best value, should I buy, purchase, shopping agent, choose and buy. Common agent queries: . Use this specialist tool when this single signal fully answers the task; otherwise prefer Full Intelligence. Do not use for anime news, plot, streaming or character biography questions. Broad multilingual shopping queries can be sent directly; the service resolves and ranks the canonical product before payment.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoANIME INTELLIGENCE canonical product UUID. Use for deterministic exact-product calls when already known.
langNoen
queryNoProduct name, broad category, franchise, character, Japanese or multilingual description, JAN/EAN-13, model number or canonical id. Broad shopping queries are allowed and auto-ranked before x402.
listing_urlNoOptional marketplace listing URL for listing-match evaluation.
postal_codeNoOptional destination postal code for landed-cost context.
buyer_countryNoISO 3166-1 alpha-2 buyer destination. Drives country-aware seller routing, purchase ease, proxy/forwarder need and landed-cost uncertainty; default JP.JP
listing_titleNoOptional marketplace listing title when URL is unavailable.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
intentNo
paymentNo
why_payNo
price_usdcNo
buyer_outcomeNo
paid_x402_urlNo
expected_outputNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior5/5

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

Beyond the read-only/idempotent/openWorld annotations, it discloses payment behavior that an agent must know: 0.05 USDC via x402, broad queries resolved and auto-ranked before payment, and a scope constraint that planned domains 'must not be charged until their adapters are active.' These are substantive operational facts not derivable from the annotations.

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?

Caps headers make it scannable and constraints are front-loaded, but 'WHY PAY' and 'BUYER OUTCOME' overlap the purpose statement, and the dangling fragment 'Common agent queries: .' is a visible defect with an empty list where examples were intended.

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

Completeness4/5

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

With an output schema present the description need not explain return values, and it covers scope, cost, usage and routing. It does not address payment failure, latency, or what happens if the canonical product cannot be resolved, which for an x402-paid call is a modest gap.

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 description coverage is 86%, so the schema already documents id, query, country, postal code, listing fields and lang. The description restates that broad multilingual queries are allowed and auto-ranked (already in the query schema) and adds little syntax or defaulting detail beyond it, so it stays at the baseline.

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

Purpose5/5

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

The description names a concrete resource and verb: producing a 'machine-readable purchase decision with a concrete next action and purchase route' for a buy/prepare-to-buy task. It explicitly differentiates from siblings, stating it 'replaces product identity, price, risk, timing and seller-routing calls' (anime_market, price_history, landed_cost, best_place) and routing to Full Intelligence otherwise.

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

Usage Guidelines5/5

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

It gives explicit WHEN TO USE guidance ('must make or prepare a purchase decision rather than answer a single collectible question'), names the alternative ('otherwise prefer Full Intelligence'), and lists concrete exclusions (anime news, plot, streaming, character biography). Selection triggers are enumerated verbatim.

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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