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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds value beyond that by disclosing the model's provenance (ML model), the one-year horizon, and — critically — that the number is exploratory and not a calibrated probability, which tells the agent how much weight to put on the return value. It stops short of stating scale, verdict categories, or coverage limits.

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?

Two short clauses with the primary output front-loaded and the interpretive caveat immediately after it; the parenthetical source note is the only incidental content and it is brief. No filler or 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?

For a single-parameter read-only tool with no output schema, the description covers what is returned (score plus safety verdict), the horizon, the source, and the reliability caveat. It would be stronger if it described the score's range or the possible verdict values, but the essentials for correct invocation are present.

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?

There is a single parameter at 100% schema description coverage, so the schema already documents rssd_id as a Federal Reserve RSSD id with an example. The description's only contribution is 'one bank', confirming the parameter selects a single institution. Baseline 3 applies since the schema carries the detail.

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?

Names a specific output (one-year failure-risk screening score plus safety verdict) and a specific scope (one bank), which is far more than a restatement of the title. It does not, however, explicitly contrast itself with the many sibling screening/aggregation tools such as high_risk_banks or risk_dashboard, so sibling differentiation is left implicit.

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 phrase 'exploratory ... screening' implies first-pass triage use and warns against treating the output as a calibrated probability, which is genuine usage context. But there is no explicit when-to-use statement, no exclusions, and no routing to alternatives like high_risk_banks (for scanning many banks) or risk_dashboard, so an agent must infer the decision boundary.

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