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 important behavioral details beyond these annotations: the scan caps at 5000 transactions per account with a 'truncated:true' flag, and the presence of a 'provider_incident' block that indicates potential incomplete data. It also clarifies that reconnecting does not fix provider issues. No contradiction with annotations.

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 relatively long but well-structured, starting with the core purpose then expanding into parameter details and behaviors. Every sentence adds value for the agent, especially given the tool's complexity (9 parameters, multiple granularities). It could be slightly more concise, but it is not overly verbose.

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 tool's complexity (9 parameters, no output schema, and annotations providing safety hints), the description is remarkably complete. It covers purpose, all parameter details, behavioral nuances (truncation, provider incidents), and provides concrete usage guidance. There are no missing pieces that would leave an agent confused.

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 0% schema description coverage, so the description must compensate. It explains the meaning of most parameters: item (targets one bank or all), from/to (ISO dates), granularity (monthly vs raw), detail (compact, rich, raw), type (BANK or CREDIT), and item_ids (bulk support). However, the 'top_n' parameter is not explicitly described, though it is implied by 'largest N each.' This is a minor gap.

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 the tool's purpose: 'Consolidated cash-flow analysis for a whole bank CONNECTION over a period, in ONE call.' It distinguishes itself from sibling tools like openfinance_list_accounts and openfinance_list_transactions by emphasizing that it resolves accounts internally and fans out transactions, so users don't need to call those tools first.

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 when to use this tool versus alternatives: 'so you do NOT need to call openfinance_list_accounts first nor carry account_id uuids between calls.' It also provides when to omit the item parameter for all banks, lists concrete use cases like 'análise anual/mensal', specifies when to use granularity 'raw' vs 'monthly', and warns about data caps and provider incidents.

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