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

Annotations already cover read-only and non-destructive behavior. The description adds useful behavioral detail beyond annotations: totals are per currency, never summed or converted, and the source is the bank account. This helps the agent understand output semantics without contradicting the 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 three short sentences: function, use case, and a key caveat. Every sentence earns its place and the essential purpose is front-loaded. No redundant or filler content.

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 rich schema and annotations, the description covers the core behavior, grouping, currency handling, and an example use case. There is no output schema, so a bit more detail about the exact return shape could help, but the description already conveys that results are grouped totals per currency.

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 100%, so parameters like from, to, top, account, and group_by are already fully documented. The description adds no parameter-level detail beyond the schema, which matches the baseline of 3 for complete schema coverage.

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 summarizes spent/received amounts over a date range for the bank account, with explicit grouping options (category, month, account, counterparty). This distinguishes it from transaction-level siblings like transactions_list and transactions_search by emphasizing aggregation and grouping.

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 gives a concrete use case ('what did I spend in August') and notes the prerequisite that data must be imported. It provides clear context for when this tool is appropriate, though it does not explicitly name alternatives or state when not to use it.

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