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josimarh

azure-mcp-pilot

by josimarh

iam_natural_language_query

Read-onlyIdempotent

Answer IAM questions in natural language by correlating Entra ID and Azure RBAC data, returning clear summaries and details from your tenant.

Instructions

Interpreta uma pergunta de IAM em linguagem natural e responde com correlação Entra + Azure. Sempre retorna resumo e detalhes compreensíveis, sem depender de frase exata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
questionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, covering the safety profile. The description adds that it always returns a summary and understandable details, and that it doesn't rely on exact phrasing, which is useful behavioral context beyond annotations. However, it doesn't disclose return format specifics, model/interpretation variability, or limitations.

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?

Two concise sentences, front-loading the core action. No wasted words, though it sacrifices clarity for brevity given the missing details.

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?

For a natural-language query tool with no output schema, 0% schema coverage, and no annotations explaining the return structure beyond safety, the description is incomplete. It doesn't explain what 'correlação Entra + Azure' produces, the expected question format, or how results are structured.

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%, and the description provides no information about the 'question' or 'limit' parameters. The description mentions 'pergunta' implicitly but doesn't explain format, constraints, or what 'limit' controls. With 2 parameters at 0% coverage, the description fails to compensate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a verb+resource ('interpreta uma pergunta de IAM em linguagem natural e responde'), which conveys it's a natural-language query tool for IAM. However, it does not differentiate itself from siblings like timeline_natural_language_query, agent_natural_language_query, pim_natural_language_query, or graph_answer_identity_question, all of which are natural-language query interfaces. The purpose is clear at a high level but lacks sibling differentiation.

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 guidance on when to use this tool versus the many sibling natural-language query tools (timeline, agent, pim, graph). The phrase 'sem depender de frase exata' is a behavioral trait, not a usage condition. No when-to-use or when-not-to-use information is provided.

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

Deploy Server

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