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Glama
Grafana MCP Server
by nks1097

grafana_identificar_padroes_erro

Groups and categorizes frequent error-message patterns in Grafana logs by app and time range to reveal recurring issues.

Instructions

  1. Agrupar e categorizar padrões frequentes de mensagens de erro nos logs.

Input Schema

NameRequiredDescriptionDefault
deNonow-2h
ateNonow
seletor_appYes
datasource_uidNo

Output Schema

NameRequiredDescriptionDefault
erroNoMensagem de erro amigável caso haja falha
dadosNoCarga útil da resposta estruturada
avisosNoLista de alertas e avisos operacionais
sucessoNoIndica se a operação foi bem-sucedida
metadadosNoMetadados da execução
id_requisicaoNoIdentificador único da operação

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.4/5.0
Behavior2/5

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

No annotations exist, so the description carries the full burden, and it discloses almost nothing: no read-only assurance, no note on cost/volume, no indication of how the time window is interpreted or what happens if the selector matches nothing. The verb 'agrupar e categorizar' implies analysis over log data but leaves the operational profile unspecified.

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

Conciseness3/5

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

A single short sentence with the action front-loaded, which is efficient. However, the fragment opens with '42.', an unexplained ordinal that costs attention and signals the text was lifted from a numbered list rather than written for the tool.

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

Completeness2/5

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. But the description omits parameter meaning, usage conditions, and behavioral profile for a four-parameter tool with zero annotation coverage. An agent could not reliably call this correctly without opening the schema and guessing.

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?

Four parameters with 0% schema description coverage and the description explains none of them. It never mentions seletor_app (required), the de/ate time-window defaults (now-2h/now), or datasource_uid. 'nos logs' gestures at the data domain but does not map to any parameter, so the agent gets no compensation for the coverage gap.

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 concrete verb pair and resource: grouping and categorizing frequent error-message patterns in logs. That is specific enough to distinguish it from raw log search, but it never names the closest siblings (grafana_pesquisar_logs, grafana_identificar_requisicoes_lentas) to clarify the boundary. The leading '42.' is a stray list artifact that adds no meaning.

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?

There is no statement of when to reach for this tool versus searching logs directly, nor any prerequisite or exclusion. The agent must infer that this is an aggregation/analysis step rather than a fetch step. The required seletor_app is not mentioned at all, so the agent has no hint about precondition upfront.

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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