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waldur

Waldur MCP Server

Official
by waldur

list_invoices

Retrieve and display all invoices from your Waldur instance to monitor billing information and manage financial records.

Instructions

List all invoices

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler function for the 'list_invoices' MCP tool. It is decorated with @mcp.tool() for registration and executes by calling the Waldur API's invoices_list function.
    @mcp.tool()
    async def list_invoices() -> list[Invoice]:
        """List all invoices"""
        return await invoices_list.asyncio(client=client)
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'List all invoices' implies a read-only operation but doesn't specify whether it requires authentication, how results are returned (e.g., pagination, sorting), or any rate limits. For a tool with zero annotation coverage, this is a significant gap in transparency.

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 'List all invoices' is extremely concise and front-loaded, consisting of a single, clear sentence with zero waste. It efficiently communicates the core action without unnecessary elaboration, making it easy for an agent to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete for effective tool use. It doesn't explain what 'all invoices' entails (e.g., scope, format of returned data), behavioral traits like error handling, or how it fits with sibling tools. For a tool with minimal structured data, more context is needed.

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?

The input schema has 0 parameters with 100% coverage, meaning there are no parameters to document. The description doesn't need to add parameter semantics beyond what the schema provides, so it meets the baseline of 4 for tools with no parameters, as it doesn't mislead or omit necessary details.

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

Purpose3/5

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

The description 'List all invoices' clearly states the verb ('list') and resource ('invoices'), making the basic purpose understandable. However, it lacks specificity about scope (e.g., time range, status filters) and doesn't differentiate from sibling tools like 'list_customers' or 'list_projects', which follow a similar pattern. It's adequate but vague.

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. There are no explicit instructions on context, prerequisites, or exclusions, and it doesn't mention sibling tools like 'query' that might offer overlapping functionality. This leaves the agent with minimal direction.

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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