Apiguru Amazon Data

Seller profiles for up to 10 seller IDs

seller_profile_batch

Read-onlyIdempotent

Use to vet sellers: name, rating and feedback counts as Amazon displays them. Returns the storefront profile for each seller id: business name, rating, feedback counts, address and marketplace presence. Price: $0.0036 per item (max 10). Seller ID validation is all-or-nothing: one malformed id rejects the entire request with 400. Every row in results is an object with status: ok (the profile), not_found (Amazon has no page for that id on this marketplace; billed, like a 404) or unavailable (could not be retrieved right now; NOT billed on the keyed path, retryable: true). A row is never null. billable_requests_count counts ok + not_found rows; on the pay-per-call rail the per-item quote is settled up front, so retry unavailable ids in a separate call rather than expecting a partial refund. On agent.apiguru.app the answer also carries success and _links.self; billable_requests_count is there on your own key only.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`geo`	No	Marketplace country code.	US
`seller_ids`	Yes	Comma-separated seller IDs, maximum 10. Each must be an Amazon seller id -- 'A' followed by 9-20 letters and digits, e.g. A2A1RNLLUK3HYA -- or the whole call 400s.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`note`	No
`results`	No
`request_id`	No
`unavailable`	No
`country_code`	No
`response_time`	No
`amazon_request_count`	No
`billable_requests_count`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 1, 2026

changedInput schema / properties / geo / enum

Previous value: -[
-  "US",
-  "CA",
-  "DE",
-  "MX",
-  "UK",
-  "FR",
-  "IT",
-  "ES",
-  "AU",
-  "BR",
-  "IN",
-  "JP",
-  "NL",
-  "AE",
-  "PL",
-  "SA",
-  "SG",
-  "SE",
-  "TR",
-  "BE"
-]New value: +[
+  "US",
+  "CA",
+  "DE",
+  "MX",
+  "UK",
+  "FR",
+  "IT",
+  "ES",
+  "AU",
+  "BR",
+  "IN",
+  "JP",
+  "NL",
+  "AE",
+  "PL",
+  "SA",
+  "SG",
+  "SE",
+  "TR",
+  "BE",
+  "IE",
+  "ZA",
+  "EG"
+]

Changed2 schema fields changedSep 28, 2026

changedInput schema / properties / seller_ids / description

Previous value: -"Comma-separated seller IDs, maximum 10. Each must be 13-15 alphanumeric characters or the whole call 400s."New value: +"Comma-separated seller IDs, maximum 10. Each must be an Amazon seller id -- 'A' followed by 9-20 letters and digits, e.g. A2A1RNLLUK3HYA -- or the whole call 400s."

changedInput schema / properties / seller_ids / pattern

Previous value: -"^[A-Za-z0-9]{13,15}(,[A-Za-z0-9]{13,15})*$"New value: +"^[Aa][A-Za-z0-9]{9,20}(,[Aa][A-Za-z0-9]{9,20})*$"

Changed2 schema fields changedSep 21, 2026

addedOutput schema / properties / note

Added value: +{
+  "default": null,
+  "title": "Note"
+}

addedOutput schema / properties / unavailable

Added value: +{
+  "default": null,
+  "title": "Unavailable"
+}

Changed1 schema field changedSep 6, 2026
- addedInput schema / properties / seller_ids / pattern
```
Added value: +"^[A-Za-z0-9]{13,15}(,[A-Za-z0-9]{13,15})*$"
```
First observedSep 5, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Goes far beyond the readOnly/idempotent annotations: discloses pricing ($0.0036/item, max 10), all-or-nothing id validation with a 400 failure mode, and the exact billing treatment of each row status (`not_found` billed, `unavailable` not billed and `retryable`). Also notes that a row is never null and where `billable_requests_count`/`_links.self` appear by rail.

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?

Front-loaded with purpose and return shape before the billing detail, and nearly every sentence carries actionable information. The pay-per-call settlement and rail-specific response fields are somewhat dense and could be tightened, but they are not filler.

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?

For a billed batch read with an output schema present, this covers everything an agent needs: input constraints, failure modes, billing consequences, and per-row status semantics. Nothing material is left to inference.

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, but the description adds behavioral meaning the schema lacks: the batch cap of 10, the all-or-nothing validation that 400s the whole call, and the Amazon seller-id format. It says nothing about `geo`, but the schema's enum fully covers that.

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?

Opens with a specific verb and audience ('Use to vet sellers') and enumerates the returned fields (business name, rating, feedback counts, address, marketplace presence) for each seller id. An agent can distinguish it from siblings like seller_reviews or search without opening any schema.

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?

Gives clear context for when to reach for it (vetting sellers) and a concrete operational rule: retry `unavailable` ids in a separate call rather than expecting a partial refund. It never names a sibling alternative explicitly (e.g. seller_reviews for review text), so it stops short of full when-not guidance.

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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