Onça Setorial

ANVISA sanctions citing one rule (Outcome Ledger)

rule_enforcement

Read-onlyIdempotent

For one ANVISA rule (RDC or IN): its publication date and source, the ANVISA sanctions in the Diário Oficial that cite it as breached (date, act url, and the company only when the act names exactly one company by CNPJ), their count, the lag from publication to the first citing sanction when observable, and, counted apart, refusals of companies' own requests that cite the rule as grounds (these are NOT sanctions). Each act counts once. Use for 'who was sanctioned under RDC 47/2013 and since when'. Needs the pharmaceutical sector licensed. Deterministic: computed from official datasets, no model in the loop.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "rule": "<rule>"
    },
    "name": "rule_enforcement"
  }
}

Input Schema

Name	Required	Description	Default
`rule`	Yes	The rule, e.g. 'RDC 47/2013', 'RDC nº 47, de 2013', 'rdc-anvisa-47:2013', 'IN 9/2014'. Without a year, every year on record for that number.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 11, 2026

TDQS

A4.1/5.0

Behavior5/5

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

Beyond the annotations (readOnly, idempotent, openWorld, non-destructive), the description discloses that results are deterministic and computed from official datasets with no model in the loop, that each act counts once, that company names are only surfaced when an act names exactly one CNPJ, and that refusals of company requests are counted separately and are explicitly NOT sanctions. These are exactly the disambiguating behaviors an agent needs to interpret output correctly.

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 with what the tool returns, followed by a use case and a determinism note; every clause carries information. The opening sentence is a long stacked list, slightly dense to parse, but not padded.

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?

There is no output schema, so the description bears the full burden of describing return values, and it does so completely: fields, counting rules, the company-attribution constraint, the lag caveat ('when observable'), and the separate refusal bucket. Nothing an agent needs in order to call or interpret this tool is missing.

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% and the schema's rule parameter already documents accepted notations ('RDC 47/2013', 'rdc-anvisa-47:2013') and the no-year fallback. The description adds no syntax or semantic detail beyond that, so baseline 3 applies.

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?

The description names a specific verb and resource — returns ANVISA sanctions in the Diário Oficial that cite one given rule — and enumerates the exact fields returned (publication date, source, act url, CNPJ-gated company, count, lag). It does not explicitly differentiate itself from siblings like enforcement_process or consultation_outcome, which keeps it from a 5.

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?

It supplies a concrete query pattern ('who was sanctioned under RDC 47/2013 and since when') and a precondition ('Needs the pharmaceutical sector licensed'), giving clear context for use. It offers no explicit when-not guidance or named alternative tool, so it is not 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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