Visão geral do mês em uma só chamada: receitas, despesas, saldo, maiores categorias de despesa, status dos limites e contas a pagar dos próximos 7 dias. Padrão: mês atual. totals são base caixa; top_expense_categories são base por lançamento e NÃO somam com totals.expenses.
| Name | Required | Description | Default |
|---|---|---|---|
| year | No | ||
| month | 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?
Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds meaningful semantic caveats: totals are cash basis, top_expense_categories are per-transaction and must not be added to totals.expenses. This is valuable behavioral nuance beyond what annotations provide, though it omits auth or rate-limit context.
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?
The description is two dense, front-loaded sentences with no filler. Every clause contributes either scope, content, default behavior, or a critical semantic warning, making it highly efficient.
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?
With no output schema, the description does well by enumerating the main result components and exposing a non-obvious aggregation mismatch. It could specify exact response key names or formatting details, but the essential information needed to call and interpret the tool is present.
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 for the two parameters. It only mentions that the default is the current month, leaving the meaning of year and month to be inferred from their names and context. This is adequate but not fully explicit about format or valid ranges.
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 clearly states a specific purpose: a single-call monthly overview with a concrete list of metrics (revenues, expenses, balance, top expense categories, limits status, and next-7-day bills). This content list effectively differentiates it from the many sibling read-only tools even without naming them.
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 implies when to use the tool through 'Visão geral do mês em uma só chamada' and the listed contents, but it does not explicitly state when to prefer this over similar siblings like get_financial_summary or get_cashflow_forecast, nor does it mention exclusions. Usage context is clear but mostly left to inference.
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.
Most tools target distinct resource+action pairs, but the reporting/query side is crowded: get_balances, transactions_list_results, get_financial_summary, get_monthly_overview, and the category/tag reports overlap heavily. Long descriptions disambiguate bases and use cases, but an agent must read carefully to avoid picking the wrong report or list variant.
Organizze tools overwhelmingly follow a consistent organizze_<verb>_<noun> snake_case pattern with create_, list_, get_, update_, and delete_ prefixes. Deviations like transactions_list_results, the mass_* versus update_transactions_* bulk variants, and unprefixed platform tools keep it from being perfect.
68 tools is far beyond the practical agent surface and includes many near-variant list/report/mass tools plus six unrelated platform-level tools. Even though the finance domain is broad, this count creates an extreme mismatch for efficient tool selection.
The core finance lifecycle is well covered: accounts, cards, categories, budgets, transactions, invoices, transfers, and reports all have substantial CRUD or equivalent support. However, some referenced operations are missing entirely, such as delete_recurrence, clear_latest_imports, and remove_from_latest_imports, and transfers/recurrences lack full lifecycle coverage.