Catálogo de instituições financeiras (bancos/operadoras) com o id (slug) usado em institution_id ao criar/editar contas e cartões. Use query para filtrar por nome.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | 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 readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds useful context about the institution_id mapping and query filtering, but it does not disclose pagination, result shape, or matching semantics. The safety profile is covered by annotations, so this is adequate but not rich.
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 front-loaded: it states the purpose, the key slug concept, and the filtering usage in two sentences with no unnecessary words.
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 read-only list tool with optional parameters, the description is largely complete: it explains why the catalog matters, how the id is used, and how to filter. The only meaningful gap is the behavior/meaning of limit.
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 missing parameter documentation. It explains query as a name filter, but limit is entirely undocumented, leaving one of two parameters without semantic guidance.
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 and resource: a catalog of financial institutions with the id (slug) used as institution_id. This clearly distinguishes it from sibling list tools such as organizze_list_accounts, organizze_list_categories, and organizze_list_credit_cards.
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 conveys when to use the tool: to obtain the institution id needed when creating or editing accounts and cards. It also gives a concrete filtering instruction with query. It does not explicitly mention alternatives, but the intended context is clear.
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.