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Hämta kundfaktura

get_customer_invoice
Read-onlyIdempotent

Hämtar en kundfaktura med alla uppgifter. Använd när du har fakturans id och behöver detaljer; för att hitta fakturor eller se flera, använd list_customer_invoices, och för obetalt per kund, använd customer_outstanding. Returnerar kund, fakturanummer, fakturadatum och förfallodag, rader, belopp och moms i öre, kvarvarande saldo, status och verifikatnummer. Läser bara, ändrar inget.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
orgnrYesBolagets organisationsnummer, 10 siffror med eller utan bindestreck, t.ex. 559900-1004. Hämta med list_companies.
invoice_idYesKundfakturans id (heltal), t.ex. 42. Hämta med list_customer_invoices.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / invoice_id / description
      Added value: +"Kundfakturans id (heltal), t.ex. 42. Hämta med list_customer_invoices."
    • addedInput schema / properties / orgnr / description
      Added value: +"Bolagets organisationsnummer, 10 siffror med eller utan bindestreck, t.ex. 559900-1004. Hämta med list_companies."
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, closed-world and non-destructive, so safety is covered; the description's 'Läser bara, ändrar inget' largely restates that. It does add genuinely useful context by enumerating the returned fields (customer, invoice number, dates, rows, amounts in öre, remaining balance, status, voucher number), which the annotations cannot convey.

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?

Front-loads purpose, then usage routing, then return shape in a tight paragraph with no filler. The return-field sentence is somewhat run-on but every element is informative.

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

Completeness5/5

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

With no output schema present, the description compensates by listing the return payload in detail, and usage/prerequisites are fully covered. An agent has everything needed to call and interpret this tool correctly.

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

Parameters3/5

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

Schema coverage is 100% and both parameters (orgnr, invoice_id) are fully documented in Swedish with formats and how to obtain them. The description adds no parameter syntax or meaning beyond the schema, so the baseline 3 applies.

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?

States a specific verb and resource ('Hämtar en kundfaktura med alla uppgifter') and explicitly distinguishes itself from two named siblings (list_customer_invoices, customer_outstanding). An agent can differentiate it from the other invoice tools without opening schemas.

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

Usage Guidelines5/5

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

Gives an explicit trigger ('Använd när du har fakturans id och behöver detaljer') plus named alternatives with their selecting conditions (list for finding/listing, customer_outstanding for unpaid per customer). Nothing is left to inference.

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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