Skip to main content
Glama
mnbro

aruba-fatturazione-elettronica-mcp

by mnbro

aruba_detect_invoice_anomalies

Read-onlyIdempotent

Identify data-quality anomalies in electronic invoices to flag potential issues, without offering definitive tax advice.

Instructions

Detect data-quality anomalies without providing definitive tax advice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
directionNoboth
date_fromNo
date_toNo
limitNo
confirm_readNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description adds limited behavioral context beyond these. The disclaimer 'without providing definitive tax advice' is useful but does not describe other behaviors like input constraints or output format. No contradictions with annotations.

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

Conciseness2/5

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

The description is extremely concise (one sentence) but sacrifices necessary information. It lacks structure and fails to convey how or when the tool should be used. Conciseness is not valuable when it omits critical details.

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

Completeness1/5

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

Given five optional parameters with zero schema descriptions, many sibling tools, and an output schema available, the description is woefully incomplete. It does not explain what anomalies are detected, how parameters affect results, or how to interpret the output. Minimal viable completeness would require at least parameter explanations.

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 0%, meaning no parameter descriptions. The tool description does not explain any of the five parameters (direction, date_from, date_to, limit, confirm_read). This provides no added value over the schema alone.

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 clearly states the tool detects data-quality anomalies, indicating a specific verb and resource (invoice data quality). However, it does not distinguish itself from sibling tools like aruba_find_duplicate_invoices or aruba_validate_invoice_xml_structure, which also detect specific quality issues. The disclaimer about tax advice adds clarity on scope.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, context, or exclude other tools. The only hint is the disclaimer, which is not usage direction.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/mnbro/aruba-fatturazione-elettronica-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server