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list_products

List and filter products from your e-commerce platforms. Search by name or SKU, paginate results, and include related data like images and variants.

Instructions

List products with filters. Returns paginated results.

IMPORTANT for AI:

  • ALWAYS use 'q' to search by name/SKU first instead of browsing all pages.

  • Use 'include' to get relations: skus,variants,images,attributes,brand,shops,combos

  • Response 'meta.pagination' has total, total_pages, current_page for pagination.

  • Platform codes: 1=shopee, 2=lazada, 3=tiktokshop, 4=tiki, 5=pancake, 6=pos

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoSearch by product name or SKU
category_idNoFilter by category ID
brand_idNoFilter by brand ID
shop_idsNoFilter by shop IDs (list)
platformNoFilter by platform (1=shopee, 2=lazada, 3=tiktokshop, 4=tiki, 5=pancake, 6=pos)
product_skuNoSearch by product SKU specifically
sku_skuNoSearch by variant SKU specifically
includeNoComma-separated relations: skus,variants,images,attributes,brand,shops,combos
sortNoSort order (default id:-1 = newest first)id:-1
limitNoPage size (default 25)
pageNoPage number (1-indexed)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations provided, the description fully explains behavior: it returns paginated results with meta.pagination, supports filters, and lists platform codes. It also specifies default sort and page size. No contradictions or omissions.

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 with a clear 'IMPORTANT for AI' section front-loading key guidance. Every sentence adds value, and the structure is efficient, covering purpose, usage, and response details in a compact format.

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?

Given 11 parameters and no output schema, the description covers essential aspects: pagination metadata, search strategies, include relations, platform codes, sorting, and defaults. It adequately prepares an AI agent for effective usage.

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. The description adds value by prioritizing the 'q' parameter for search efficiency and listing acceptable values for 'include' (e.g., skus,variants,images). It also clarifies platform codes. However, deeper parameter details are already in the schema.

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 'List products with filters' and specifies 'Returns paginated results', using a specific verb and resource. It distinguishes from sibling tools like 'search_all_products' and 'get_product' by implying a listing function with filters.

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: 'ALWAYS use q to search by name/SKU first instead of browsing all pages' and recommends using 'include' for relations. However, it does not mention when to use this tool over siblings like 'search_all_products' or when not to use it, leaving some ambiguity.

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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