Matriz de faturas (mês × cartão) com totais por mês, por cartão e total geral, usando os mesmos valores de get_credit_card_invoices. Use quando o usuário pedir faturas de VÁRIOS cartões e/ou meses, em vez de somar à mão. Padrão: ano atual, todos os cartões.
| Name | Required | Description | Default |
|---|---|---|---|
| cards | No | ||
| end_date | No | ||
| start_date | 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 this a read-only, idempotent, non-destructive operation, so the bar is lower. The description adds useful behavioral context: the output is a matrix with totals, values match get_credit_card_invoices, and the default is the current year for all cards.
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 compact and well-structured: what the tool returns, when to use it, and its default behavior. There is no redundant wording or repetition of the schema.
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 read-only aggregation tool with zero required parameters, the description covers the core needs: output shape, relationship to related values, intended use, and defaults. It does not go into date formats or edge cases, but the provided context is reasonably complete given the annotations and optional parameters.
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 coverage is 0%, so the description must compensate. It conveys that cards default to all cards and the date range defaults to the current year, but it does not explain the expected date format or how card identifiers are specified. This is enough for the safe default call but insufficient for custom filters.
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 that the tool produces an invoice matrix organized by month and credit card, including per-month, per-card, and overall totals. It also references get_credit_card_invoices to clarify the underlying values, distinguishing this aggregation view from other invoice tools.
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 explicitly tells the agent to use this tool when the user asks for invoices across multiple cards and/or months, rather than summing manually. It gives a clear usage context but does not explicitly state when to prefer the sibling get_credit_card_invoices for a single card or month.
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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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.