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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds useful context: data comes from NCUA call reports, quarter defaults to latest, and it is keyless. No contradictions; it enriches the behavioral understanding.

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 dense and front-loaded with the purpose and metrics, followed by answer examples and usage hints. It is slightly long but each sentence earns its place, including the empty-object example. Could be trimmed slightly but remains efficient.

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?

With no output schema, the description lists the exact metrics returned (number of credit unions, assets, members, average size), which tells the agent what to expect. It covers optional parameters and historical querying. It doesn't specify error handling or invalid state codes, but for a simple aggregation tool with 2 optional params, it's sufficiently complete.

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 coverage is 100%, with both state and quarter described. The description reinforces that quarter defaults to latest and state is optional with examples. It adds minimal new semantics beyond the schema, so a 3 (baseline) 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 clearly states the tool aggregates industry totals (number of credit unions, assets, members, average size) for the US or a specific state, with example questions. It distinguishes itself from NCUA sibling tools like ncua_credit_union_financials (per-credit-union) and ncua_search_credit_unions (individual lookup) by focusing on aggregate industry data.

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 tells the agent when to use it (for aggregate industry questions like 'how many credit unions in Texas') and how to query historical quarters. It does not explicitly name alternative tools or exclusions, but the scope is clear enough against the sibling set. A slightly more explicit 'use this instead of...' would push it to 5.

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