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Fatture in Cloud MCP Server

Fatture in Cloud MCP Server

receipts_monthly_totals

Read-only

Retrieve monthly totals of sales or till receipts for a given year, with optional company filtering, to summarize annual receipt revenue by month.

Instructions

Totali mensili dei corrispettivi (scontrini o ricevute) di un anno.

Input Schema

NameRequiredDescriptionDefault
typeNotill_receipt
yearYes
company_idNoAzienda su cui operare. Default: FIC_COMPANY_ID o l'unica azienda del token

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.1

TDQS

B3.4/5.0
Behavior3/5

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

readOnlyHint=true already establishes the safety profile, and the description confirms the read-only, aggregated nature of the result. It does not cover defaults (company_id resolution from token/FIC_COMPANY_ID), what happens when no receipts exist for the year, or the shape of the returned totals – and no output schema exists to fill that gap.

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?

A single short sentence with no filler, front-loading the resource and the aggregation level. It is efficient, though it is perhaps too terse for a three-parameter aggregation tool.

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

Completeness3/5

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

For a small, read-only aggregation tool the description covers the essential intent, but with no output schema the agent gets no indication of the return structure (per-month rows, currency, grouping by receipt type). The gaps are modest rather than disqualifying.

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 only 33%, so the description should carry more weight. It does tie 'di un anno' to the required year parameter and alludes to the type enum by naming both scontrini and ricevute, but it does not map those terms to sales_receipt vs till_receipt or explain the default of till_receipt. company_id is documented only by the schema.

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 specific resource (corrispettivi / scontrini o ricevute) and a specific aggregation (totali mensili) scoped to one year, which is enough to tell it apart from list_receipts or get_receipt. It stops short of naming any sibling explicitly, so differentiation is inferential rather than stated.

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 aggregation vocabulary implies the use case (monthly rollup rather than per-document retrieval), but there is no explicit when-to-use or when-not-to-use guidance and no pointer to alternatives such as revenue_summary or preview_totals. The agent has to infer routing from the name.

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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