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list_products

Retrieve and filter products from Siigo's inventory with pagination controls. Use code or name filters to find specific items in the product catalog.

Instructions

List products with pagination and optional filters.

Args: page: Page number (starts at 1) page_size: Number of results per page (max 100) code: Filter by product code (partial match) name: Filter by product name (partial match)

Returns paginated list of products with navigation links.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
page_sizeNo
codeNo
nameNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The core handler function for the "list_products" tool. It is decorated with @mcp.tool, accepts pagination and filter parameters, constructs query params, and calls the Siigo API /products endpoint.
    @mcp.tool
    async def list_products(
        ctx: Context,
        page: int = 1,
        page_size: int = 25,
        code: str | None = None,
        name: str | None = None,
    ) -> dict[str, Any]:
        """List products with pagination and optional filters.
    
        Args:
            page: Page number (starts at 1)
            page_size: Number of results per page (max 100)
            code: Filter by product code (partial match)
            name: Filter by product name (partial match)
    
        Returns paginated list of products with navigation links.
        """
        params: dict[str, Any] = {"page": page, "page_size": min(page_size, 100)}
        if code:
            params["code"] = code
        if name:
            params["name"] = name
    
        return await get_client(ctx).get("/products", params=params)
  • Dynamic registration of the "list_products" tool in the lazy-loading tool function map used by discovery and execution meta-tools.
    "list_products": products.list_products,
  • Tool discovery schema entry providing metadata (name, category, summary) for the "list_products" tool, used by list_siigo_tools.
    {"name": "list_products", "category": "products", "summary": "List products with pagination and filters"},
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits like pagination, filtering (partial match), and return format with navigation links, which goes beyond basic functionality. However, it lacks details on rate limits, error conditions, or authentication requirements.

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 well-structured and front-loaded with the core purpose, followed by clear parameter explanations and return information. Every sentence adds value with no wasted words, making it efficient and easy to parse.

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 tool's complexity (4 parameters, pagination, filtering) and the presence of an output schema, the description is largely complete. It covers key aspects like parameter semantics and return format, though it could benefit from more behavioral context like error handling or performance notes.

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?

The description adds significant meaning beyond the input schema, which has 0% description coverage. It explains all four parameters (page, page_size, code, name) with semantics like 'starts at 1', 'max 100', and 'partial match', fully compensating for the schema's lack of descriptions.

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 with a specific verb ('List') and resource ('products'), and distinguishes it from sibling tools like 'get_product' by emphasizing pagination and filtering capabilities. It explicitly describes what the tool does beyond just the name.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context through the mention of pagination and filtering, but does not explicitly state when to use this tool versus alternatives like 'get_product' or other list_* siblings. No guidance on prerequisites or exclusions is provided.

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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