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openapi_v2_ecommerce_rerank

Rerank documents for ecommerce search queries

Rerank a list of product documents by relevance to ecommerce search queries.

Use this to improve product search result ordering. Pass one or more search queries and a shared list of product documents (titles, descriptions, or concatenated attributes). The model scores each document against each query and returns them sorted by relevance. Powered by a fine-tuned Qwen3-Reranker model optimized for ecommerce product matching.

Credits: 1 credit per query in the batch. A request with 3 queries costs 3 credits.

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": {
      "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[EcommerceRerankResult]",
  "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
topKNoReturn only the top K most relevant documents per query. Omit to return all documents ranked.
queriesYesList of search queries to rerank documents against. Max 10 queries per request.
documentsYesList of document lists, one per query (documents[i] is reranked against queries[i]). Max 100 documents per query.

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description must carry the transparency burden. It discloses the scoring mechanism, the underlying model, and credit costs, but it also contains a misleading phrase: 'shared list of product documents' while the input schema requires a list of document lists per query. This inconsistency undermines the agent's understanding of actual behavior.

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 main human-readable description is concise and front-loaded with a clear one-liner followed by essential details and credit information. However, the inclusion of a large, redundant response schema block (which does not even detail the 'data' payload) makes the overall description longer than necessary without adding much actionable value.

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

Completeness3/5

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

The tool is moderately complex with multiple queries and document lists, and no annotations are present. While the input schema is thorough and the response schema is included, the description fails to clarify the exact structure of the 'data' field (the actual reranked results), and the 'shared list' misstatement leaves the usage ambiguous. More examples or a clearer description of the output would be needed for full completeness.

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?

Input schema coverage is 100%, so the baseline is 3. The description adds some context (documents can be titles, descriptions, or attributes) and explains credit costs, but it doesn't compensate for the schema's clarity because it introduces the contradictory 'shared list' notion. The schema's own descriptions are more precise.

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 uses a specific verb+resource ('Rerank documents for ecommerce search queries') and clearly states its purpose: to improve product search result ordering. It distinguishes itself from sibling search tools by focusing on reranking an existing list of product documents, not searching from scratch.

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 explicitly says 'Use this to improve product search result ordering,' providing clear context for when to invoke this tool. It also explains how to use it (pass queries and documents), but it does not mention alternative tools or when not to use it, stopping short of a full usage guideline.

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