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fluig_dataset_admin

Retrieve administrative dataset metadata and source code to verify scheduling, sync status, update intervals, and active/draft versions before debugging or modifying a dataset.

Instructions

Metadados ADMIN de dataset (o que a tela Datasets mostra): serverOffline, updateInterval, jobLastExecution/jobNextExecution, syncStatus, active/draft. Com code=true traz também o código-fonte. É por AQUI que se descobre se um dataset está agendado — agendamento = serverOffline:true + trigger no Quartz.

Input Schema

NameRequiredDescriptionDefault
envYesOBRIGATÓRIO. Ambiente alvo: "teste" (homologação, o host de FLUIG_HOST) ou "prod" (PRODUÇÃO REAL, o host de FLUIG_HOST_PROD). Não há default: a escolha é sempre explícita, para que ninguém leia homologação achando que é produção nem escreva em produção achando que é teste.
codeNotrue inclui o datasetImpl (código-fonte)
searchNofiltro por id/descrição (substring). Vazio = lista tudo.
pageSizeNopadrão 30

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.3.0

TDQS

A3.9/5.0
Behavior4/5

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

No annotations exist, so the description carries the burden, and it does disclose the returned metadata fields plus conditional behavior (code=true includes datasetImpl source). It omits permission/auth requirements and does not explicitly state it is a read-only, side-effect-free operation, leaving a gap for a no-annotation tool.

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?

Three compact sentences, front-loaded with the resource and field list, followed by the conditional code=true note and the key scheduling interpretation. No filler, though the field enumeration is slightly dense.

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?

With no output schema and no annotations, the description sufficiently describes the returned metadata and the critical interpretation rule (serverOffline + Quartz trigger). It lacks read-only framing and permission notes, which would complete the picture for a four-parameter admin tool.

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%, so all four parameters are already documented, establishing a baseline of 3. The description adds only the code=true behavior, which the schema also states, so no meaningful semantics are added beyond structured fields.

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?

States a clear verb-scoped resource: admin metadata of a dataset (what the Datasets screen shows), and enumerates the concrete fields returned (serverOffline, updateInterval, jobLastExecution/jobNextExecution, syncStatus, active/draft). It implies differentiation from the plain list/get siblings via 'Metadados ADMIN' and 'É por AQUI que se descobre se um dataset está agendado', but never names a sibling explicitly.

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

Usage Guidelines4/5

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

Gives a concrete use case: this is the tool to determine whether a dataset is scheduled, with the rule that scheduling = serverOffline:true + Quartz trigger. No explicit exclusions or named alternatives (e.g., vs fluig_dataset_list or fluig_dataset_get), so it stops short of a 5.

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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