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Amazon Product

glim_amazon_get
Read-onlyIdempotent

Fetch Amazon product detail from a full product URL (the marketplace - com|co.uk|de|fr|es|it - is read from the URL host; pass the url field from a glim_amazon_search result, or any /dp/ page URL). Returns title, buybox price (gross + VAT-excluded net), stock, delivery estimate, rating, top reviews, and an 'other sellers' summary (count + floor price). Text mode (default) returns a compact view with offers_summary {buybox, lowest_new, lowest_used} - pass format='json' for full structured data incl. the offers[] listing and images.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refYesFull Amazon product URL - pass the `url` from a glim_amazon_search result, or any /dp/<ASIN> product page URL. The URL carries the marketplace (amazon.de, amazon.co.uk, ...), so no separate region is needed; tracking junk in the URL is ignored. A bare ASIN is rejected: it is ambiguous across marketplaces.
formatNoOutput format. 'text' (default): compact human-readable view, fewer tokens. 'json': the same product as machine-readable JSON, plus the fields text omits: the full `offers[]` list (text summarizes it), `images[]`, and variation/other-seller detail.text

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / format / description
      Previous value: -"Output format. 'text' (default): compact human-readable view, fewer tokens. 'json': full structured data (offers[], images, variants)."New value: +"Output format. 'text' (default): compact human-readable view, fewer tokens. 'json': the same product as machine-readable JSON, plus the fields text omits: the full `offers[]` list (text summarizes it), `images[]`, and variation/other-seller detail."
  2. Changed2 schema fields changed
    • changedInput schema / properties / ref / description
      Previous value: -"Amazon product URL or 10-char ASIN (e.g. https://www.amazon.com/dp/B0F59XT8QM or B0F59XT8QM). Obtain real ASINs from glim_amazon_search; do not invent them."New value: +"Full Amazon product URL - pass the `url` from a glim_amazon_search result, or any /dp/<ASIN> product page URL. The URL carries the marketplace (amazon.de, amazon.co.uk, ...), so no separate region is needed; tracking junk in the URL is ignored. A bare ASIN is rejected: it is ambiguous across marketplaces."
    • removedInput schema / properties / tld
      Removed value: -{
      -  "default": "com",
      -  "description": "Amazon marketplace: com | co.uk | de | fr | es | it",
      -  "enum": [
      -    "com",
      -    "co.uk",
      -    "de",
      -    "fr",
      -    "es",
      -    "it"
      -  ],
      -  "type": "string"
      -}
  3. Changed2 schema fields changed
    • removedInput schema / properties / currency
      Removed value: -{
      -  "description": "Override display currency. Validated against per-tld allow-list.",
      -  "type": "string"
      -}
    • removedInput schema / properties / geo
      Removed value: -{
      -  "description": "Postal code for region-accurate pricing and delivery dates",
      -  "type": "string"
      -}
  4. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint, so the safety profile is clear. The description adds valuable behavioral details: the marketplace is parsed from the URL host, tracking junk is ignored, and format affects output structure. No contradictions.

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 a single, well-structured paragraph that presents the main purpose first, then details about the URL and return fields. It is informative without unnecessary verbosity, though could be slightly more terse.

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?

Despite no output schema, the description thoroughly lists all major return fields (title, price, stock, etc.) and distinguishes text vs JSON format. Given the tool's complexity and two parameters, the description is complete enough for an agent to understand what to expect.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds meaning beyond the schema by explaining that 'ref' must be a full URL carrying the marketplace and rejecting bare ASINs, and that 'format' controls whether offers[] and images[] are included. This adds practical guidance.

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 clearly states the tool fetches Amazon product detail from a full product URL, listing specific returned fields (title, price, etc.) and implicitly distinguishes from glim_amazon_search by requiring a URL rather than search terms.

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

Usage Guidelines4/5

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

The description explains that the URL should come from a glim_amazon_search 'url' field or any /dp/<ASIN> page URL, and that bare ASINs are rejected. It does not explicitly state when not to use this tool or mention alternatives, but the context is clear.

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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