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

The description discloses important behavioral traits beyond the annotations (readOnlyHint, idempotentHint, destructiveHint). It warns about a 5000/account cap with truncation flag, a provider_incident block that can cause incomplete data, and explains the fan-out internal logic. This fully informs the agent about side effects and limitations, adding significant value over the annotations alone.

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 front-loaded with the core purpose in the first sentence. It is lengthy but every sentence adds value, covering parameters, behavior, and edge cases. Some rephrasing could improve readability (e.g., using bullets), but overall it is well-structured and informative without redundancy.

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?

Given the complexity (9 unannotated parameters, no output schema), the description is exceptionally complete. It explains all parameters, return structure (summary fields like total entradas, por_mes, top_despesas, by_account), edge cases (truncation, provider incidents), and bulk support via item_ids. No critical information is missing for an agent to select and invoke this tool correctly.

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?

The input schema has 9 parameters with no descriptions (0% coverage), but the description provides thorough explanations for each parameter: item (connector_id/connector_name/item_id), from/to (ISO dates), granularity (monthly/raw), detail (compact/rich/raw), type (BANK/CREDIT), top_n, item_id, item_ids. It gives exact usage examples and behavioral details, fully compensating for the lack of schema descriptions.

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 this tool provides consolidated cash-flow analysis for a bank connection over a period in one call, resolving accounts internally and avoiding the need for separate list_accounts calls. It distinguishes itself from siblings like openfinance_list_accounts and openfinance_list_transactions by emphasizing the consolidated, one-call nature. The verb 'analyze' and resource 'connection transactions' are specific and 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 explicitly states when to use this tool (e.g., for 'análise anual/mensal', 'fluxo de caixa', 'entradas e saídas', 'maiores gastos/recebimentos') and provides guidance on parameters like granularity and detail for different needs. It mentions that you do NOT need to call openfinance_list_accounts first. However, it does not explicitly mention alternative sibling tools for simpler queries, which would strengthen usage boundaries.

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