Valida os dados de uma etapa de cotação por ramo SEM CRIAR NADA (usa o validador oficial da Agger, que não persiste). Retorna os campos inválidos/obrigatórios. Chame SEM 'dados' para descobrir o que a etapa exige, ou COM os dados preenchidos para conferir antes de cotar.
| Name | Required | Description | Default |
|---|---|---|---|
| ramo | Yes | ||
| dados | No | ||
| secao | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnly/idempotent/destructive annotations, the description adds meaningful behavior: it uses the official Agger validator, does not persist anything, returns invalid/required fields, and reveals how omitting vs providing 'dados' changes behavior. This fully discloses the tool's side-effect-free nature and output intent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences, no filler, with the most important safety qualifier ('SEM CRIAR NADA') front-loaded. Every sentence adds useful information about purpose, return value, or invocation strategy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 3-parameter tool with no output schema, the description covers purpose, return behavior, and both usage modes. The main gap is that 'secao' is not explicitly connected to 'etapa', and the expected format of 'dados' is not clarified, but the tool remains callable with reasonable inference from the schema enums.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 explains 'dados' behavior well and maps 'ramo' to the branch being quoted, but it never explicitly names the 'secao' parameter, even though 'etapa' likely refers to it. This leaves one parameter under-documented and forces the agent to infer the mapping.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Valida'), resource ('dados de uma etapa de cotação por ramo'), and explicitly clarifies it creates nothing. It clearly distinguishes this validation tool from any creation or persistence flow, making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit call patterns: call without 'dados' to discover requirements, or with 'dados' to validate before quoting. It does not name an alternative tool, but the usage modes are clear enough that an agent knows when to invoke it. It lacks an explicit when-not-to-use statement, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct function: CEP lookup, quote validation, dashboard stats, account listing, business listing, insurer listing, and separate platform utilities for auth, connectivity, marketplace, bug reports, version, and toolkit state. No two tools overlap in purpose, so an agent can clearly differentiate them.
Tool names mix conventions: some are bare nouns (agger_cep, agger_negocios, marketplace), some use verb_noun (agger_list_accounts, report_bug, show_version), one is noun_verb (agger_cotacao_validar), and several are generic single verbs (authenticate, connect). This inconsistency makes the naming pattern unpredictable and harder to infer.
The 12-tool set is well-scoped: 6 domain-specific Agger tools cover the core insurance broker workflows, and 6 generic platform tools handle authentication, connectivity, marketplace operations, and diagnostics. Each tool earns its place without unnecessary bloat.
The domain coverage is partial: the server supports listing businesses, validating quotes, and viewing insurers, but lacks create/update/delete operations for quotes or detailed single-item views. Some gaps exist (e.g., no create quote, no get_business_detail), but agents can work around them by using the list and validation tools, and the platform utilities address meta-level needs.