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

Goes well beyond the annotations by disclosing exclusion rules (pending transactions omitted), the sign convention for income vs expenses, and partial-failure behavior via the `warnings` array with reconnect_url for banks that could not contribute. That partial-data disclosure is genuinely valuable for a read tool whose correctness depends on bank connectivity; only rate limits or historical-range limits are unaddressed.

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?

Four sentences, each carrying distinct payload: result shape first, then the pending-transaction exclusion, then sign semantics, then the warnings contract. Front-loaded with the primary output and free of repetition.

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?

There is no output schema, so the description carries the return-shape burden and does so completely: the metrics, the top-5 lists, and the `warnings` array with its message/reconnect_url fields. Combined with full schema coverage on inputs and readOnly/idempotent annotations, an agent has everything needed to call and interpret it.

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% — both `month` (YYYY-MM with example) and `account_id` (with a pointer to list_accounts) are fully documented in the schema. The description adds no parameter-level detail beyond what is already structured, so baseline 3 applies.

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 names the resource precisely (income, expenses, net for one calendar month across connected accounts) and even specifies the aggregation depth (top 5 income sources and expense categories). It is immediately distinguishable from transaction-level siblings, though it never explicitly contrasts with the closer sibling get_spending_summary.

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?

Usage is implied by the output shape — an agent can infer this is the tool for monthly aggregate figures rather than raw transactions. However, there is no explicit when-to-use/when-not guidance and no mention of the natural alternative (get_spending_summary) for budgeting-style breakdowns, so the choice must be inferred.

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