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More AI - ChatGPT & Claude MCP (Fortnox)

Momskontroll

check_vat
Read-onlyIdempotent

Momskontroll: försäljning per momssats mot bokförd utgående moms, omvänd skattskyldighet, momskonton som inte nollställts, och EU-tröskeln. Example question: "Stämmer momsen inför deklarationen?" Computed on the server from live Fortnox data (Fortnox API, https://api.fortnox.se/apidocs), over all pages.

Input Schema

NameRequiredDescriptionDefault
toNosista månad ÅÅÅÅ-MM, standard samma som from Month, YYYY-MM.
fromNoförsta månad ÅÅÅÅ-MM, standard förra månaden Month, YYYY-MM.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / from / description
      Previous value: -"första månad ÅÅÅÅ-MM, standard förra månaden"New value: +"första månad ÅÅÅÅ-MM, standard förra månaden Month, YYYY-MM."
    • changedInput schema / properties / to / description
      Previous value: -"sista månad ÅÅÅÅ-MM, standard samma som from"New value: +"sista månad ÅÅÅÅ-MM, standard samma som from Month, YYYY-MM."
  2. Added

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely non-obvious context: the result is computed server-side from live Fortnox data and traverses all pages, so the agent knows results are complete and not a partial page sample.

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 scope of the check is front-loaded, followed by a usage example and a provenance note; every clause contributes. The mixed Swedish/English phrasing and the dense enumeration make it slightly harder to scan than it could be.

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?

An output schema exists, so return values need not be described, and both parameters are fully documented in the schema. The remaining gap is the missing relation to get_vat_return_boxes, which matters because that sibling is the natural next step after this check.

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 description coverage is 100% and both from/to already document their YYYY-MM format and default behavior. The description adds nothing about the period parameters, so this sits at the baseline where the schema carries the load.

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 names a concrete analysis (VAT check) and enumerates the four specific checks it performs: sales per VAT rate vs booked output VAT, reverse charge, un-cleared VAT accounts, and the EU threshold. That is far more specific than the title alone. It does not, however, state how it differs from the closely related sibling get_vat_return_boxes, so an agent must infer the boundary.

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 example question "Stämmer momsen inför deklarationen?" implies the pre-declaration reconciliation use case, which is useful. But there is no explicit when-to-use/when-not guidance and no routing to get_vat_return_boxes, the obvious alternative for producing the actual VAT return figures.

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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