APIClaw

openapi_v2_products_search

Products Search V2

Search Amazon products by keyword, category, and multi-dimensional filters.

Use this to discover products in a specific niche, analyze competitor listings, or find high-demand low-competition opportunities. Example: search "yoga mat" in Sports & Outdoors with monthlySalesFloor >= 500 and price <= $30 to find proven sellers in an affordable range. Data is based on the latest daily snapshot; results are paginated (max 100 per page). Related: /products/competitors for competitor analysis, /products/history for trends.

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

Name	Required	Description	Default
`page`	No	Page number
`badges`	No	Include products with these badges. Example: ['bestSeller', 'amazonChoice', 'newRelease', 'aPlus', 'video'].
`bsrMax`	No	Maximum Best Sellers Rank. Example: 100000.
`bsrMin`	No	Minimum Best Sellers Rank (lower = better). Example: 1.
`lqsMax`	No	Maximum Listing Quality Score
`lqsMin`	No	Minimum Listing Quality Score
`sortBy`	No	Sort field	monthlySalesFloor
`keyword`	No	Search keyword
`pageSize`	No	Page size
`priceMax`	No	Maximum product price. Example: 99.99.
`priceMin`	No	Minimum product price. Example: 9.99.
`dateRange`	No	Aggregation window for metrics like monthly sales, revenue, and rating count. Null or '30d' — last 30 days (default). 'YYYY-MM' — that calendar month, e.g. '2026-04'. Available months: '2026-02' up to the most recent completed month.
`fbaFeeMax`	No	Maximum FBA fee. Example: 15.00.
`fbaFeeMin`	No	Minimum FBA fee. Example: 3.00.
`ratingMax`	No	Maximum star rating (0.0-5.0). Example: 5.0.
`ratingMin`	No	Minimum star rating (0.0-5.0). Example: 4.0.
`sortOrder`	No	Sort direction: asc or desc	desc
`subBsrMax`	No	Maximum sub-category BSR. Example: 50000.
`subBsrMin`	No	Minimum sub-category BSR. Example: 1.
`listingAge`	No	Max product age: '30d', '90d', '180d', '1y', '2y'. Null = no limit.
`qaCountMax`	No	Maximum Q&A count. Example: 100.
`qaCountMin`	No	Minimum Q&A count. Example: 5.
`marketplace`	No	Amazon marketplace code. Only 'US' is currently supported.	US
`categoryPath`	No	Category hierarchy from root to current level (e.g., ['Electronics', 'Computers', 'Laptops'])
`fulfillments`	No	Fulfillment filter. Example: ['FBA', 'FBM'].
`excludeBadges`	No	Exclude products with these badges. Supported: ['aPlus', 'video'].
`excludeBrands`	No	Brand names to exclude. Example: ['Generic'].
`includeBrands`	No	Brand names to include. Example: ['Apple', 'Samsung'].
`excludeSellers`	No	Seller names to exclude.
`includeSellers`	No	Seller names to include. Example: ['Apple Store'].
`ratingCountMax`	No	Maximum total rating count. Example: 10000.
`ratingCountMin`	No	Minimum total rating count. Example: 50.
`sellerCountMax`	No	Maximum number of sellers. Example: 20.
`sellerCountMin`	No	Minimum number of sellers. Example: 1.
`excludeKeywords`	No	Keywords to exclude from results. Example: ['refurbished', 'used'].
`monthlySalesMax`	No	Maximum monthly sales floor. Units sold. Example: 5000.
`monthlySalesMin`	No	Minimum monthly sales floor. Units sold. Example: 100.
`variantCountMax`	No	Maximum number of product variants. Example: 50.
`variantCountMin`	No	Minimum number of product variants. Example: 2.
`bsrGrowthRateMax`	No	Maximum BSR growth rate as decimal.
`bsrGrowthRateMin`	No	Minimum BSR growth rate as decimal. Example: -0.2 = 20% improvement.
`keywordMatchType`	No	Keyword match type: 'fuzzy', 'phrase', or 'exact'. Null = fuzzy.
`onlyCategoryRank`	No	If true, only return products ranked in their category BSR.
`monthlyRevenueMax`	No	Maximum monthly revenue floor. Example: 50000.00.
`monthlyRevenueMin`	No	Minimum monthly revenue floor. Example: 1000.00.
`ratingFilterTarget`	No	Choose whether rating-related filters apply to the current product or the most-rated variant.
`salesGrowthRateMax`	No	Maximum sales growth rate as decimal. Example: 0.5 = 50% growth.
`salesGrowthRateMin`	No	Minimum sales growth rate as decimal. Example: 0.1 = 10% growth.
`ratingToSalesRateMax`	No	Maximum rating-to-sales rate as decimal. Example: 0.5.
`ratingToSalesRateMin`	No	Minimum rating-to-sales rate as decimal. Example: 0.05.
`monthlyRatingCountMax`	No	Maximum monthly new rating count. Example: 500.
`monthlyRatingCountMin`	No	Minimum monthly new rating count. Example: 10.
`parentMonthlySalesMax`	No	Maximum parent ASIN monthly sales floor. Units sold.
`parentMonthlySalesMin`	No	Minimum parent ASIN monthly sales floor. Units sold.

TDQS

A3.9/5.0

Behavior4/5

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

With no annotations, the description carries the full burden. It discloses that data is a daily snapshot and results are paginated with a max of 100 per page. It also embeds the response schema (showing pagination metadata and credits), though it does not discuss rate limits or explicitly state read-only behavior. The prose adds meaningful behavioral context beyond the schema.

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

Conciseness2/5

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

The prose is concise and front-loaded, but the description includes a massive '### Responses' section with full response schemas, ADR credit details, and TODO comments. This bloat detracts from conciseness. Every sentence and line does not earn its place; much of the response schema is unnecessary for tool selection.

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?

Given the complexity (54 parameters, no annotations, no output schema), the description covers purpose, usage, data freshness, pagination, and related tools. It includes response schemas to compensate for the missing output schema. Minor gaps exist (e.g., whether keyword is required), but overall it is quite 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?

Schema description coverage is 100%, so the baseline is 3. The description adds a concrete example using monthlySalesFloor and price, which maps to monthlySalesMin and priceMax, but it does not explain any parameters beyond what the schema already provides. No new semantic meaning is added.

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 begins with 'Products Search V2' and a clear verb-resource-scope statement: 'Search Amazon products by keyword, category, and multi-dimensional filters.' It distinguishes the tool from siblings by naming related endpoints for competitors and history, and the use cases (niche discovery, competitor listing analysis, opportunity finding) give specific context.

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 states when to use the tool ('Use this to discover products in a specific niche, analyze competitor listings, or find high-demand low-competition opportunities') and provides a concrete filter example. It also mentions related endpoints for competitor analysis and trends, but stops short of explicitly saying 'do not use this for X; use Y instead.'

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

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