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

Annotations already mark the tool readOnly and idempotent, and the description adds useful behavior beyond that: amounts are normalized from thousands to whole US dollars and access is keyless. This is the kind of operational context that helps an agent set expectations.

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 its purpose and stays tight through examples. It is a bit long relative to the simple interface, but every sentence adds either intended-use or output-normalization context.

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?

The core call pattern is demonstrated with name/cert and metric examples, and keyless access is stated to address auth. However, because the schema lists no required parameters, it is not explicit that a metric plus an identifier is required, or what happens on ambiguous matches; with no output schema this leaves minor ambiguity.

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?

Input schema coverage is 100%, so the baseline is 3; the schema already documents cert, name, idrssd, and the metric list. The description restates the metric choices and gives examples, but adds little parameter-level meaning beyond what the schema provides.

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 a specific action and resource: track one US bank call report line item over time. It immediately scopes the tool to single-bank, single-metric time series, which separates it from siblings like ffiec_call_report and ffiec_compare_banks.

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 natural-language examples ('how have this bank's deposits changed', 'net income trend for bank X') clearly communicate the intended use case. There are no explicit when-not-to-use notes or named alternatives, so it stops short of a 5.

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