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list_journals

Retrieve and filter accounting journal entries with pagination to manage financial records in Siigo's electronic invoicing system.

Instructions

List journal entries (accounting vouchers) with pagination.

Args: page: Page number (starts at 1) page_size: Number of results per page (max 100) date_start: Filter by start date (YYYY-MM-DD format) date_end: Filter by end date (YYYY-MM-DD format)

Returns paginated list of journal entries with navigation links.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
page_sizeNo
date_startNo
date_endNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Core handler function for list_journals tool: handles parameters, calls Siigo API /journals endpoint with pagination and date filters.
    @mcp.tool
    async def list_journals(
        ctx: Context,
        page: int = 1,
        page_size: int = 25,
        date_start: str | None = None,
        date_end: str | None = None,
    ) -> dict[str, Any]:
        """List journal entries (accounting vouchers) with pagination.
    
        Args:
            page: Page number (starts at 1)
            page_size: Number of results per page (max 100)
            date_start: Filter by start date (YYYY-MM-DD format)
            date_end: Filter by end date (YYYY-MM-DD format)
    
        Returns paginated list of journal entries with navigation links.
        """
        params: dict[str, Any] = {"page": page, "page_size": min(page_size, 100)}
        if date_start:
            params["date_start"] = date_start
        if date_end:
            params["date_end"] = date_end
    
        return await get_client(ctx).get("/journals", params=params)
  • Maps tool name 'list_journals' to its implementation in journals.list_journals for dynamic/lazy tool execution.
    "list_journals": journals.list_journals,
  • Tool index metadata defining name, category, and summary for discovery and list_siigo_tools.
    {"name": "list_journals", "category": "journals", "summary": "List journal entries with pagination"},
Behavior4/5

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

With no annotations provided, the description carries the full burden. It effectively discloses key behavioral traits: pagination behavior (page/page_size parameters), date filtering capabilities, and the return format (paginated list with navigation links). It doesn't mention rate limits, authentication needs, or error conditions, but covers the core operational behavior well.

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

Conciseness4/5

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

The description is well-structured with a clear opening sentence followed by parameter details and return information. Every sentence adds value, though the 'Args:' section could be slightly more integrated. It's appropriately sized for a tool with 4 parameters and pagination behavior.

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 (pagination, filtering), no annotations, but with an output schema present, the description provides good coverage. It explains what the tool does, all parameters, and the return structure. The output schema will handle return value details, so the description doesn't need to duplicate that information.

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?

With 0% schema description coverage, the description fully compensates by explaining all 4 parameters clearly. It adds essential semantics beyond the bare schema: page numbering starts at 1, page_size has a maximum of 100, date filters use YYYY-MM-DD format, and parameters are optional (implied by 'Filter by'). This provides complete parameter understanding.

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 ('journal entries/accounting vouchers'), making the purpose immediately understandable. It distinguishes itself from sibling tools like 'get_journal' (singular) by indicating it returns multiple entries with pagination. However, it doesn't explicitly contrast with other list_* tools 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 Guidelines3/5

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

The description implies usage through the mention of pagination and date filtering, suggesting this is for browsing multiple journal entries. However, it provides no explicit guidance on when to use this versus alternatives like 'get_journal' (singular) or other list_* tools, nor does it mention prerequisites or exclusions.

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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