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Glama

verificar_texto

Extracts normative citations from a draft and checks each against covered official sources, flagging found, ambiguous, nonexistent, or manual-confirmation cases to prevent hallucinated references.

Instructions

Extrai citações normativas de um texto e verifica cada uma (anti-alucinação).

Estado por citação: encontrada | ambigua | inexistente | requer_conferencia (provável, só conferível por quem consulta) | indisponivel (não é inexistência). Citação fora das fontes cobertas não é validada. Use para revisar uma minuta inteira; para uma citação só, verificar_citacao. Limites: texto ≤ 100.000 caracteres; até 200 citações. Pode gravar cache local.

Input Schema

NameRequiredDescriptionDefault
dataNo
textoYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.3/5.0
Behavior4/5

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

No annotations, so the description carries the burden, and it discloses the most important behavior: the enumerated per-citation states including the subtle distinction that 'indisponivel' is not the same as 'inexistente', plus hard limits (100,000 chars, 200 citations) and the fact that it may write a local cache. Missing only whether the operation otherwise mutates anything or requires configuration.

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?

Tight, front-loaded, and organized into purpose, state taxonomy, routing rule, and limits with no wasted prose. The state enumeration is somewhat dense in a single run-on line, but every clause carries information.

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

Completeness4/5

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

The output schema covers return values and the description covers scope, limits, states, and the sibling alternative, which is nearly everything needed to call it correctly. The one real gap is the undocumented 'data' parameter, which matters for a verification tool where the reference date could change results.

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 coverage is 0%, so the description must compensate. It does partly – the text length limit restates the schema's maxLength and the 200-citation cap is genuinely new – but the 'data' parameter is left entirely unexplained in both schema and description, leaving the agent to guess its purpose and format.

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?

States a specific verb pair and resource: extracts normative citations from a text and verifies each one (anti-hallucination). This is clearly distinct from the sibling verificar_citacao, which it names explicitly as the single-citation alternative.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit routing rule: use this for reviewing an entire draft, use verificar_citacao for a single citation. It also sets a scope boundary – citations outside covered sources are simply not validated rather than reported as failures.

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