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ThiagoJacobLannes

brasil-planos-saude-mcp

operator_profile

Retrieves ANS data for a single health-plan operator—registration, complaints, IDSS quality, access bands, fines, and readjustments—to help judge whether it is a good choice.

Instructions

Everything ANS publishes about one health-plan operator, to judge whether it is a good choice.

Use for "is Hapvida good?", "how does Unimed Campinas rank on complaints?", "has SulAmérica been fined?". Returns:

  • registration: legal name, CNPJ, modality, head office, phone, status (active or cancelled, with date and reason), beneficiaries and size class;

  • complaints (IGR): latest month, 12-month average, the median of operators of the same size, the operator's position among them, and the monthly series;

  • quality (IDSS, 0-1, higher is better) for the last 5 years with its four dimensions;

  • access-to-care monitoring band (0 best, 3 worst) for the last published quarters;

  • fines applied by ANS: totals, last 5 years, status and the most recent cases;

  • the readjustment applied to its small-group pool (contracts with < 30 lives).

Args: operator: Name (or part of it), CNPJ, or ANS registry number. If the name matches several operators, the largest active one is used and the others are listed in outras_operadoras_com_nome_parecido: check it is the one the user meant (Unimed, for example, is hundreds of separate cooperatives). coverage: "medica" or "odonto". Default: every coverage the operator has.

Always quote the month/year of each figure and explain that IGR is lower-is-better and IDSS higher-is-better (see como_ler in the result).

Input Schema

NameRequiredDescriptionDefault
coverageNo
operatorYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the burden well: it discloses the full data scope (six domains), the meaning of directionality (IGR lower-is-better, IDSS higher-is-better), and an important silent fallback ('the largest active one is used') with a pointer to outras_operadoras_com_nome_parecido for verification. It omits any statement about permissions, rate limits, or read-only nature, which keeps it short of a 5.

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?

Front-loaded purpose, then a scannable bulleted return breakdown, then args — good ordering with no filler sentences. The per-field return enumeration is somewhat long given an output schema already exists, which is the main redundancy.

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

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An agent has everything needed to call it correctly: input formats, ambiguity handling, coverage default, and interpretation guidance for the returned metrics (with a pointer to como_ler). Since an output schema exists, the description is not obliged to enumerate return fields further.

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

Parameters5/5

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

Schema coverage is 0%, so the description must do all the work and it does: 'operator' accepts name/partial name, CNPJ, or ANS registry number, and it explains the multi-match resolution behavior. 'coverage' gets its two allowed values ('medica'/'odonto') and its default, which the schema's untyped anyOf string/null cannot convey.

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?

Opens with a specific verb-scoped statement: 'Everything ANS publishes about one health-plan operator', plus the decision it supports. It is clearly an entity-detail tool and is distinguishable from siblings like compare_operators or rank_operators, which act on multiple operators.

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?

Example questions ('is Hapvida good?', 'has SulAmérica been fined?') make the intended use case concrete and give the agent a trigger pattern. It does not explicitly state when to prefer find_operators or compare_operators instead, so the routing guidance is implied rather than spelled out.

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