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list_customers

Retrieve and filter customer data from Siigo's electronic invoicing system using pagination, name, or identification number parameters.

Instructions

List customers with pagination and optional filters.

Args: page: Page number (starts at 1) page_size: Number of results per page (max 100) name: Filter by customer name (partial match) identification: Filter by identification number (NIT/cédula)

Returns paginated list of customers with navigation links.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
page_sizeNo
nameNo
identificationNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The implementation of the list_customers tool handler, which calls the Siigo API to list customers with optional pagination and filters.
    @mcp.tool
    async def list_customers(
        ctx: Context,
        page: int = 1,
        page_size: int = 25,
        name: str | None = None,
        identification: str | None = None,
    ) -> dict[str, Any]:
        """List customers with pagination and optional filters.
    
        Args:
            page: Page number (starts at 1)
            page_size: Number of results per page (max 100)
            name: Filter by customer name (partial match)
            identification: Filter by identification number (NIT/cédula)
    
        Returns paginated list of customers with navigation links.
        """
        params: dict[str, Any] = {"page": page, "page_size": min(page_size, 100)}
        if name:
            params["name"] = name
        if identification:
            params["identification"] = identification
    
        return await get_client(ctx).get("/customers", params=params)
  • Import statement that loads the customers module in non-lazy mode, triggering registration of the list_customers tool via @mcp.tool decorator.
    from siigo_mcp.tools import customers  # noqa: E402, F401
  • Mapping of 'list_customers' to its handler function in the lazy-loading _tool_functions dictionary.
    "list_customers": customers.list_customers,
  • Discovery metadata entry for the list_customers tool, providing name, category, and summary for dynamic tool listing.
    {"name": "list_customers", "category": "customers", "summary": "List customers 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 full burden. It discloses pagination behavior and filtering options, but lacks details about authentication requirements, rate limits, error conditions, or what specific data fields are returned in the paginated list. The mention of 'navigation links' hints at pagination structure but isn't fully explanatory.

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 efficiently structured with a clear purpose statement followed by parameter explanations and return information. Every sentence adds value, and the Args/Returns formatting helps readability without unnecessary verbosity.

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 moderate complexity (4 parameters, pagination, filtering) and the presence of an output schema (which handles return value documentation), the description provides adequate context. It covers the core functionality and parameter meanings well, though additional behavioral details would enhance completeness.

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?

With 0% schema description coverage, the description must compensate. It successfully explains all 4 parameters: page (starts at 1), page_size (max 100), name (partial match filter), and identification (NIT/cédula filter). This adds crucial semantic context beyond the bare schema types and defaults.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('List') and resource ('customers'), and specifies pagination and filtering capabilities. It distinguishes itself from 'get_customer' (singular retrieval) by indicating it returns multiple customers, but doesn't explicitly contrast with other list tools like 'list_credit_notes' or 'list_invoices' beyond the resource type.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose 'list_customers' over 'get_customer' (singular retrieval) or other list tools, nor does it specify prerequisites or contextual constraints for usage.

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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