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Eqvitta

Eqvitta Accounting MCP Server

by Eqvitta

create_logistic_invoice

Generate a freight/transport invoice with freight amount, GST, party details, destination, and notes for accurate billing.

Instructions

Create a freight/transport invoice. CREATE ONLY. CRITICAL FOR CLAUDE: When this tool succeeds, you MUST output the EXACT text returned by the tool verbatim in a clean copyable message without converting it into tables or adding extra markdown summaries, so the user can easily copy and send the full invoice notification message directly to the party.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNo
notesNo
gst_rateNo
party_idNo
company_idYes
party_nameNoShipper name
destinationNo
bilty_numberNo
freight_amountYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

B3.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the critical post-success behavior (output the exact returned text verbatim), which is a valuable behavioral trait. However, it omits other aspects like permissions, side effects, or response format beyond the verbatim instruction. The description does not contradict annotations (none exist).

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

Conciseness3/5

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

The description consists of two sentences. The first is concise and purposeful, but the second is long and detailed, containing the critical output instruction. While not excessively verbose, the structure could be improved by separating the behavioral instruction into a more structured format. It is still reasonably efficient.

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?

For a mutation tool with 9 parameters, no annotations, and no output schema, the description is insufficient. It does not explain what happens on success beyond the verbatim output instruction, nor does it describe prerequisites, parameter meanings, or the overall invoice creation process. An agent would lack essential context to correctly invoke the tool.

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

Parameters1/5

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

Schema description coverage is only 11% (one parameter has a description). The tool description adds no information about parameters, leaving the agent to infer meanings from names alone. It fails to compensate for the low schema coverage, which is a significant gap for a 9-parameter create tool.

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 creates a freight/transport invoice, distinguishing it from sibling creation tools like create_sales_invoice or create_purchase_invoice. The verb 'create' and resource 'freight/transport invoice' are specific and unambiguous.

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 implies usage for freight/transport scenarios via the resource name, and the sibling context reinforces this distinction. However, it does not explicitly state when not to use this tool or mention alternatives, leaving some room for interpretation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.