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

With annotations already declaring readOnlyHint=true and idempotentHint=true, the safety profile is covered. The description adds valuable behavioral context: it discloses that state-only requests use a privacy-preserving self-hosted aggregate while filtered requests hit the live OpenFEMA API, and it clarifies the privacy posture of not redistributing claim-level records. It doesn't mention edge cases like an empty request or rate limits, but the core behavioral distinction is well explained.

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 sentences with zero filler. The first sentence states what the tool is and the key behavioral split; the second gives a use case. Information is front-loaded and every clause earns its place.

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 read-only, no-output-schema tool, the description covers the essentials: data source, filtering modes, and privacy implications. The only gap is that it doesn't specify behavior when no parameters are provided (all params are optional), and it doesn't report return value structure, but the rules state output schema absence doesn't burden the description. Overall, an agent can correctly invoke this tool for common scenarios.

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%, so the baseline is 3. The description adds meaning beyond the schema by explaining how parameters interact: a state-only request (just 'state') triggers a different data source than zip/county/year filters. This conditional behavior is not encoded in the schema and is important for selecting the correct invocation.

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 identifies the resource (National Flood Insurance Program claim history) and the two operational modes based on filter usage. It distinguishes this tool from siblings like flood_zone_lookup by focusing on claim history rather than zones. The phrase 'without redistributing claim-level records' adds a precise scope that separates it from potential record-redistribution tools.

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 provides a clear use case ('assessing prior loss patterns') and explains when to use each backend (state-only vs. zip/county/year). However, it does not explicitly name alternative tools or state when not to use this tool, leaving exclusion to inference rather than direct guidance.

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