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openapi_v2_products_leaderboard

Products Leaderboard V2

Return a product-level Top-N leaderboard for a category.

sales ranks by monthly sales, surging by sales growth, and newRelease ranks Amazon New Release products by monthly sales. Related: /products/search for custom filters and sorting.

Responses:

200: Successful Response (Success Response) Content-Type: application/json

Example Response:

{
  "success": true,
  "meta": {
    "requestId": "Requestid",
    "timestamp": "Timestamp"
  }
}

Output Schema:

{
  "properties": {
    "success": {
      "type": "boolean",
      "title": "Success",
      "description": "Whether the request was successful",
      "default": true
    },
    "data": {
      "title": "Data",
      "description": "Response data payload"
    },
    "error": {
      "description": "Error details if request failed"
    },
    "meta": {
      "description": "Metadata for API responses.\n\nCredit fields follow the ADR-0003 parallel-fields strategy (Option 3):\n- `credits_remaining` / `credits_consumed` (int): legacy fields, rounded\n  to whole credits, kept for zero-breaking-change to existing SDK clients.\n- `credits_remaining_exact` / `credits_consumed_exact` (float): new\n  precision-aware fields for clients that opt in to decimal credits.\n\nSee ADR-0003 decision 5 and the \u00a78 deprecation timeline.\n\nTODO(2026-11, ADR-0003 \u00a78 +6mo): mark `credits_remaining` /\n`credits_consumed` as `deprecated=True` in their Field() definitions\nand announce in customer changelog.\nTODO(2027-05, ADR-0003 \u00a78 +12mo): remove the legacy int fields via a\nmajor-version bump of the OpenAPI surface.",
      "properties": {
        "requestId": {
          "type": "string",
          "title": "Requestid",
          "description": "Unique request identifier"
        },
        "timestamp": {
          "type": "string",
          "title": "Timestamp",
          "description": "Response timestamp in ISO 8601 format"
        },
        "total": {
          "title": "Total",
          "description": "Total number of records"
        },
        "page": {
          "title": "Page",
          "description": "Current page number"
        },
        "pageSize": {
          "title": "Pagesize",
          "description": "Number of records per page"
        },
        "totalPages": {
          "title": "Totalpages",
          "description": "Total number of pages"
        },
        "creditsRemaining": {
          "title": "Creditsremaining",
          "description": "Remaining API credits (rounded to whole credits; see creditsRemainingExact for precise value)"
        },
        "creditsConsumed": {
          "title": "Creditsconsumed",
          "description": "Credits consumed by this request (rounded; see creditsConsumedExact for precise value)"
        },
        "creditsRemainingExact": {
          "title": "Creditsremainingexact",
          "description": "Remaining API credits, precise to 1 decimal place"
        },
        "creditsConsumedExact": {
          "title": "Creditsconsumedexact",
          "description": "Credits consumed by this request, precise to 1 decimal place"
        },
        "tokensUsage": {
          "description": "Provider token-usage block \u2014 populated on terminal video polls only, null on every non-video endpoint. See TokensUsage for its fields."
        }
      },
      "type": "object",
      "required": [
        "requestId",
        "timestamp"
      ],
      "title": "ResponseMeta"
    }
  },
  "type": "object",
  "required": [
    "meta"
  ],
  "title": "OpenApiResponse[list[Product]]",
  "examples": []
}

422: Validation Error Content-Type: application/json

Example Response:

{
  "detail": [
    {
      "loc": [],
      "msg": "Message",
      "type": "Error Type",
      "ctx": {}
    }
  ]
}

Output Schema:

{
  "properties": {
    "detail": {
      "items": {
        "properties": {
          "loc": {
            "items": {},
            "type": "array",
            "title": "Location"
          },
          "msg": {
            "type": "string",
            "title": "Message"
          },
          "type": {
            "type": "string",
            "title": "Error Type"
          },
          "input": {
            "title": "Input"
          },
          "ctx": {
            "type": "object",
            "title": "Context"
          }
        },
        "type": "object",
        "required": [
          "loc",
          "msg",
          "type"
        ],
        "title": "ValidationError"
      },
      "type": "array",
      "title": "Detail"
    }
  },
  "type": "object",
  "title": "HTTPValidationError"
}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageSizeNoNumber of ranked products to return.
rankTypeYesLeaderboard type: sales, surging sales, or Amazon New Release products.
dateRangeNoNull or '30d' for the latest snapshot, or an available YYYY-MM month.
marketplaceNoAmazon marketplace code. Only 'US' is currently supported.US
categoryPathYesCategory hierarchy from root to the target category.

TDQS

A4.5/5.0
Behavior4/5

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

The description is transparent about the operation being a read-only query (no side effects mentioned). It does not hide any potential costs or limitations beyond what is inherent in the request. Since no annotations are provided, the description carries the burden, and it does not mislead.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured: it starts with the core purpose, then details the rank types in a bullet-like style, and ends with a related tool reference. No redundant or vague phrasing.

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?

The description covers the essential context: what the tool does, how rank types differ, and a pointer to an alternative. It does not explicitly mention pagination or the output structure, but the input schema already includes pageSize and the output schema is provided in the response section. This is sufficient for a simple read endpoint.

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

Parameters5/5

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

All parameters have descriptions in the schema, and the tool description adds extra clarity, especially for the rankType parameter by explaining what each enum value means in business terms. This goes beyond the schema's basic description, providing full semantic value.

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's function: 'Return a product-level Top-N leaderboard for a category.' It also specifies the different rank types (sales, surging, newRelease) with their meanings, distinguishing it from other product-related tools like search.

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 provides guidance on when to use this tool versus alternatives by mentioning 'Related: /products/search for custom filters and sorting.' This implies that the leaderboard is for predefined ranking types, while search is for custom queries. However, it doesn't explicitly state conditions for choosing one over the other, so a small deduction.

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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TDQS

B3.2/5.0
Disambiguation2/5

Several tools have unclear boundaries, most notably openapi_v2_competitor_product_keywords and openapi_v2_product_traffic_terms, which have identical descriptions. The deprecated openapi_v2_realtime_product duplicates openapi_v3_realtime_product, and openapi_v2_image_embedding overlaps heavily with openapi_v2_fashion_image_embedding.

Naming Consistency2/5

Naming is inconsistent: a few tools follow a clean verb_noun pattern (create_video_asset, list_video_assets, poll_video_task), while the vast majority are prefixed with openapi_v2_/openapi_v3_ followed by nouns or mixed verbs. The route-style prefix is not a meaningful verb and creates an arbitrary split across the tool set.

Tool Count2/5

49 tools is far beyond the well-scoped range and spans multiple unrelated domains (Amazon product data, TikTok commerce, fashion vision, web scraping, video generation, billing). The server appears to be an entire REST API surface exposed wholesale rather than a curated set of capabilities.

Completeness3/5

Each domain is individually fairly complete (Amazon search/reviews/keywords/VoC, TikTok search, web tools, video generation), but there are notable gaps: video assets lack update/delete, video tasks lack cancel/list, and there is no singular 'get daily product by ASIN' alongside the realtime variants. The broad scope makes it hard to verify full lifecycle coverage across all domains.

Resources