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openapi_v2_competitors

Competitor Lookup V2

Search competitor products by keyword, brand, ASIN, or category with filters.

Use this to identify competing products around a specific listing or brand. Example: pass asin="B07FR2V8SH" to find all products competing in the same keywords and category. Data is based on the latest daily snapshot; results are paginated (max 100 per page). Related: /products/search for broader keyword discovery.

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
asinNoAmazon Standard Identification Number (10-char alphanumeric). Example: 'B07FR2V8SH'.
pageNoPage number
badgesNoInclude products with these badges. Example: ['bestSeller', 'amazonChoice', 'newRelease', 'aPlus', 'video'].
sortByNoSort fieldmonthlySalesFloor
keywordNoSearch keyword
pageSizeNoPage size
brandNameNoFilter by brand name.
dateRangeNoAggregation window for metrics like monthly sales, revenue, and rating count. '30d' (default) — last 30 days. 'YYYY-MM' — that calendar month, e.g. '2026-04'. Available months: '2026-02' up to the most recent completed month.30d
sortOrderNoSort direction: asc or descdesc
sellerNameNoFilter by seller name.
marketplaceNoAmazon marketplace code. Only 'US' is currently supported.US
categoryPathNoCategory hierarchy from root to current level (e.g., ['Electronics', 'Computers', 'Laptops'])
fulfillmentsNoFulfillment filter. Example: ['FBA', 'FBM'].
excludeBadgesNoExclude products with these badges. Supported: ['aPlus', 'video'].
excludeBrandsNoBrand names to exclude. Example: ['Generic'].
includeBrandsNoBrand names to include. Example: ['Apple', 'Samsung'].
excludeSellersNoSeller names to exclude.
includeSellersNoSeller names to include. Example: ['Apple Store'].
sellerCountMaxNoMaximum number of sellers. Example: 20.
sellerCountMinNoMinimum number of sellers. Example: 1.
excludeKeywordsNoKeywords to exclude from results. Example: ['refurbished', 'used'].
keywordMatchTypeNoKeyword match type: 'fuzzy', 'phrase', or 'exact'. Null = fuzzy.

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 carries the full burden. It mentions pagination ('results are paginated (max 100 per page)') and data freshness ('Data is based on the latest daily snapshot'), which is useful. However, it does not explicitly disclose whether the operation is read-only or any side effects, though that is implied by 'search'. Given search tools typically don't have hidden destructive behavior, the disclosure is adequate but not thorough.

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

Conciseness3/5

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

The opening description is concise (four sentences), but the overall description field includes large response schemas and examples that significantly bulk it up. While the response schemas are potentially useful, they are verbose and could distract from the core usage guidance. The key information is front-loaded, but the length beyond that reduces its conciseness.

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, when to use it, an example, pagination details, and related tools. It mentions the daily snapshot and pagination limits. The output schema is provided (though not as a separate field, it is embedded in the description), which helps the agent understand the response. Given the high complexity (22 parameters) the description does reasonably well, but it could also mention constraints like the US marketplace or required vs optional, but those are already in the schema. Overall, it is fairly complete.

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?

The input schema description coverage is 100%, meaning each of the 22 parameters is already documented in the schema. The description does not add much beyond what the schema provides—it mentions the general search dimensions (keyword, brand, ASIN, category) and gives an example with 'asin', but does not elaborate on meaning of individual filters. Since the schema already covers the semantics, this scores at the baseline 3.

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 purpose: 'Search competitor products by keyword, brand, ASIN, or category with filters.' It provides a concrete example with an ASIN and distinguishes itself from the sibling/search tool by mentioning 'Related: /products/search for broader keyword discovery.' This is a specific verb+resource, well-scoped, and clearly differentiates from alternatives.

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 gives explicit guidance on when to use it: 'Use this to identify competing products around a specific listing or brand.' It also gives an example (pass asin=...) and mentions the alternative for broader discovery ('Related: /products/search for broader keyword discovery'), which is good contextual direction, though it doesn't state when NOT to use it.

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