Show Bank Deep Dive Dashboard

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

Annotations already declare readOnly, idempotent, non-destructive, and open-world hints. The description adds useful behavioral context by explaining that ChatGPT renders an interactive widget while Claude and other clients render Markdown, and it clarifies the dashboard's content categories. It does not go deeper into data freshness, error behavior, or source-specific caveats, so it provides moderate but not rich transparency.

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 two tight sentences with no filler. The primary usage guidance is front-loaded, followed by the client-specific rendering caveat that an agent needs to set expectations correctly.

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 low-complexity tool with two parameters, an output schema, and safety-relevant annotations, the description provides enough context to invoke it correctly and describe the result. It could be slightly stronger by noting how this dashboard differs from sibling institution-level tools, but nothing critical is missing for basic correct use.

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 already fully describes both parameters: cert as the FDIC Certificate Number and repdte as an optional YYYYMMDD report date with a default. The description adds no additional parameter meaning beyond implying a single-institution scope, so the baseline of 3 is appropriate.

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 states a specific use case: rendering a scannable single-institution dashboard with identity, financial metrics, risk signals, and source links. It clearly names the resource and output format, but does not explicitly distinguish this from siblings like fdic_get_institution or fdic_search_institutions, leaving some differentiation to inference.

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 opening phrase 'Use this when the user wants...' gives clear context for when the tool is appropriate, and the content list (identity, metrics, risk signals, source links) helps an agent select it. However, it does not state when not to use it or name alternatives, so it stops short of full routing guidance.

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