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markonu

last-mile-mcp

by markonu

prepare_invoice

Creates a draft invoice for a customer and amount, held for human review and issuance, ensuring irreversible billing actions require human approval.

Instructions

Prepare an invoice. It is held as a draft and is NEVER issued by this server.

An issued invoice reaches the customer and cannot be recalled, so it is the canonical irreversible action: the tool prepares, a human issues.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
amount_eurYes
customer_idYes
descriptionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations, the description carries the full behavioral burden, and it succeeds. It discloses the critical draft-only behavior, emphasizes the irreversible nature of issued invoices, and explicitly states the server never issues. This is substantial behavioral context beyond the schema.

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 short, front-loaded with the core action, and every sentence earns its place. The critical 'draft, NEVER issued' distinction appears immediately, and the second paragraph adds necessary context without fluff.

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?

For a simple three-parameter tool, the description covers the essential behavioral context and the irreversible-action boundary. An output schema exists, so return values need no explanation. It could be more complete by mentioning preconditions like an existing customer or how the draft is later accessed, but these are not critical for invoking the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description provides no parameter-level explanation. The parameter names are somewhat self-explanatory, but the description does not clarify expected formats, constraints, or relationships such as whether customer_id must be resolved via find_customer. The description fails to compensate for the missing schema 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 names a specific verb and resource: 'Prepare an invoice.' It further differentiates itself from any issuing or listing tool by explicitly stating the result is 'held as a draft' and 'NEVER issued by this server,' which separates it from siblings like customer_invoices. This is a clear, distinct purpose.

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 provides clear context that this tool is for the preparatory draft step only, with the strong boundary 'the tool prepares, a human issues.' It implies when to use it and warns against expecting issuance, but it does not explicitly name an alternative tool or state when to choose a different sibling. Clear context, but no formal 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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