Skip to main content
Glama
Erryb95

aras-plm-mcp

by Erryb95

aras_check_effectivity

Verify part validity on a given date using effective and superseded date fields.

Instructions

Verifica se una Part era valida a una certa data, in base a effective_date e superseded_date. E' l'effettivita' basata sulle date, quella che Aras popola sempre. Per l'effettivita' configurabile per modello/unita' usa aras_get_effectivity_config.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesData in formato ISO, es. '2026-01-15'
partIdsYesid delle Part da verificare
Behavior3/5

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

With no annotations, the description carries the behavioral disclosure burden. It adds meaningful context about the date-based mechanism and that this is the effectivity Aras always populates. However, it does not disclose the return shape, how missing dates are handled, or whether invalid partIds produce errors, leaving some behavioral uncertainty.

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

Conciseness5/5

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

The description is compact and front-loaded: it states the core function first, then the differentiating nuance, then the alternative. Every sentence earns its place with no redundancy.

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?

For a low-complexity check tool with two well-documented parameters, the description provides enough context to select and invoke it correctly. It could have mentioned the result format, but the core purpose, method, and sibling distinction are present.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds value beyond the schema by explaining that validity is determined by effective_date and superseded_date, which clarifies how the 'data' parameter maps to the underlying Aras effectivity logic.

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 uses a specific verb ('Verifica se una Part era valida') and identifies the resource (Part) and the temporal criterion (a certain date). It also explicitly differentiates itself from aras_get_effectivity_config, so an agent can distinguish it without opening the schema.

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?

The description states the exact use case: checking date-based effectivity using effective_date and superseded_date. It also gives an explicit alternative with the condition: use aras_get_effectivity_config for configurable model/unit-based effectivity. This is clear when-to-use and when-not-to-use guidance.

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/Erryb95/aras-plm-mcp'

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