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nks1097
by nks1097

grafana_explorar_atributos_trace

Extract and tabulate tags, HTTP attributes, and embedded errors from the spans of a trace to inspect trace details and diagnose issues.

Instructions

  1. Extrair e tabular tags, atributos HTTP e erros embutidos nos spans de um trace.

Input Schema

NameRequiredDescriptionDefault
trace_idYes
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

C2.8/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses that this is an extraction/tabulation read operation and scopes it to spans of one trace, but says nothing about datasource selection defaults, permissions, or rate behavior; the output schema covers the return shape.

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 efficient sentence, but the leading '46.' is a leftover list artifact that adds no meaning, and the brevity comes at the cost of under-specification rather than economy.

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 are covered, but for a tool with zero annotations and zero parameter documentation, the description does not do enough: no datasource guidance, no usage context, and no differentiation from trace siblings.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It implies trace_id indirectly via 'de um trace', but never mentions datasource_uid or its null default, leaving half the parameters undocumented anywhere.

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 specific verb (extrair/tabular) and concrete resources (tags, HTTP attributes, embedded errors in spans of a trace). An agent can tell what it does, though the definition never distinguishes it from trace siblings such as grafana_obter_detalhes_trace or grafana_comparar_traces.

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 phrase 'de um trace' implies a trace_id is needed, but there is no explicit when-to-use, when-not-to-use, or alternative named. With several trace-oriented siblings present, the absence of routing guidance is a real gap.

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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