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ANIME INTELLIGENCE / AI PURCHASE INTELLIGENCE

by io.github.Mike05102
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ANIME INTELLIGENCE - Collectible Rarity & Rerelease Risk

anime_rarity
Read-onlyIdempotent

Estimate scarcity and rerelease/replenishment risk for the exact Japanese collectible, not just the franchise. Combines matched supply, price premium, release age and limited-edition signals so an agent can avoid paying a false rarity premium. WHEN TO USE: Use before paying a scarcity premium for limited, discontinued, old, prize, card or hard-to-find merchandise where a future rerelease could destroy the premium. WHY PAY: Pay when scarcity or rerelease risk can change whether a premium is justified; raw listing counts alone are not enough. BUYER OUTCOME: A scarcity judgment with rerelease/replenishment context. Price: 0.01 USDC via x402. Selection triggers: rare, rarity, scarce, limited, hard to find, discontinued, rerelease, re-release, restock, premium justified. Common agent queries: is this anime figure rare | is this Nendoroid actually scarce | will this figure be rereleased | is the scarcity premium justified | check restock or rerelease risk for this collectible. 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. Changed1 schema field changed
    • changedInput schema / properties / buyer_country / description
      Previous value: -"ISO 3166-1 alpha-2 buyer destination. JP is fully supported as a first-class domestic-buyer case; default JP."New value: +"ISO 3166-1 alpha-2 buyer destination. Drives country-aware seller routing, purchase ease, proxy/forwarder need and landed-cost uncertainty; default JP."
  2. Changed1 schema field changed
    • changedInput schema / properties / lang / enum
      Previous value: -[
-  "ja",
-  "en",
-  "zh",
-  "ko",
-  "es",
-  "fr",
-  "de",
-  "it",
-  "pt",
-  "id",
-  "th",
-  "ru",
-  "ar",
-  "hi",
-  "vi",
-  "tr",
-  "nl",
-  "pl"
-]New value: +[
+  "ja",
+  "en",
+  "zh",
+  "ko",
+  "es",
+  "fr",
+  "de"
+]
  3. Changed4 schema fields changed
    • addedInput schema / properties / buyer_country
      Added value: +{
+  "default": "JP",
+  "description": "ISO 3166-1 alpha-2 buyer destination. JP is fully supported as a first-class domestic-buyer case; default JP.",
+  "type": "string"
+}
    • addedInput schema / properties / listing_title
      Added value: +{
+  "description": "Optional marketplace listing title when URL is unavailable.",
+  "type": "string"
+}
    • addedInput schema / properties / listing_url
      Added value: +{
+  "description": "Optional marketplace listing URL for listing-match evaluation.",
+  "type": "string"
+}
    • addedInput schema / properties / postal_code
      Added value: +{
+  "description": "Optional destination postal code for landed-cost context.",
+  "type": "string"
+}
  4. Changed3 schema fields changed
    • changedInput schema / properties / id / description
      Previous value: -"ANIME INTELLIGENCE canonical product UUID."New value: +"ANIME INTELLIGENCE canonical product UUID. Use for deterministic exact-product calls when already known."
    • addedOutput schema / properties / buyer_outcome
      Added value: +{
+  "type": [
+    "string",
+    "null"
+  ]
+}
    • addedOutput schema / properties / why_pay
      Added value: +{
+  "type": "string"
+}
  5. Changed2 schema fields changed
    • changedInput schema / properties / query / description
      Previous value: -"Exact product name, JAN/EAN-13 or model number. For broad requests use search_anime_product first and pass its canonical id."New value: +"Product 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."
    • changedInput schema / properties / query / examples
      Previous value: -[
-  "ONE PIECE 一番くじ 限定 A賞",
-  "Nendoroid 1000",
-  "limited anime collaboration sneaker"
-]New value: +[
+  "Is this exact ONE PIECE prize actually rare?",
+  "Rerelease risk for this Nendoroid",
+  "Is the scarcity premium justified for this Japanese collectible?"
+]
  6. Changed1 schema field changed
    • changedInput schema / properties / query / description
      Previous value: -"Product name, JAN/EAN-13, model number or identifying description."New value: +"Exact product name, JAN/EAN-13 or model number. For broad requests use search_anime_product first and pass its canonical id."
  7. Changed1 schema field changed
    • changedInput schema / properties / lang / enum
      Previous value: -[
-  "ja",
-  "en",
-  "zh",
-  "ko"
-]New value: +[
+  "ja",
+  "en",
+  "zh",
+  "ko",
+  "es",
+  "fr",
+  "de",
+  "it",
+  "pt",
+  "id",
+  "th",
+  "ru",
+  "ar",
+  "hi",
+  "vi",
+  "tr",
+  "nl",
+  "pl"
+]
  8. Changed1 schema field changed
    • changedInput schema / properties / query / examples
      Previous value: -[
-  "ONE PIECE 一番くじ 限定 A賞",
-  "Nendoroid 1000",
-  "limited anime collaboration sneaker"
-]New value: +[
+  "ONE PIECE 一番くじ 限定 A賞",
+  "Nendoroid 1000",
+  "limited anime collaboration sneaker"
+]
  9. Changed1 schema field changed
    • changedInput schema / properties / query / examples
      Previous value: -[
-  "limited Megahouse figure",
-  "Nendoroid 1000"
-]New value: +[
+  "ONE PIECE 一番くじ 限定 A賞",
+  "Nendoroid 1000",
+  "limited anime collaboration sneaker"
+]
  10. Added
  11. Removed
  12. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, so the safety profile is covered. The description adds meaningful behavioral context beyond that: the 0.01 USDC x402 cost, the fact that broad multilingual queries are auto-resolved and ranked to a canonical product before payment, and the warning about avoiding a 'false rarity premium.' This goes well beyond the structured annotations.

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?

The description is long but carefully structured with labeled sections: WHEN TO USE, WHY PAY, BUYER OUTCOME, Price, Selection triggers, Common agent queries, and exclusion rules. It is front-loaded with the core purpose. Some redundancy exists between selection triggers and common queries, but the structure makes the length digestible and useful.

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

Completeness5/5

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

Given the tool's complexity, seven parameters, and an output schema, the description covers everything needed for correct invocation: purpose, payment, canonical product resolution, alternatives, exclusions, and sample queries. The output schema handles return-value documentation, so the description does not need to explain that separately. Nothing critical is missing.

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%, well above the 80% threshold, so the schema already documents most parameters. The description reinforces that queries can be broad and are auto-ranked, but most per-parameter meaning lives in the schema. Baseline 3 is appropriate because the description adds purpose context rather than new parameter-level semantics.

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 opens with a specific verb and resource: 'Estimate scarcity and rerelease/replenishment risk for the exact Japanese collectible, not just the franchise.' It clearly differentiates from sibling tools by emphasizing exact-product analysis rather than franchise-level data and by naming Full Intelligence as the broader alternative. This lets an agent understand the tool's unique role without needing to inspect other definitions.

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?

The description explicitly provides 'WHEN TO USE', 'WHY PAY', selection triggers, common agent queries, and a direct routing rule: 'Use this specialist tool when this single signal fully answers the task; otherwise prefer Full Intelligence.' It also states what the tool is not for ('anime news, plot, streaming or character biography questions'). This is exemplary usage guidance with both positive and negative conditions.

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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