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

Annotations already cover the read-only and non-destructive profile, and the description adds relevant context by naming the exact NOAA NCEI source, disclosing the $0.02 USDC per-call cost, and summarizing the returned trend information. This goes beyond the structured annotations without contradicting them.

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 the strongest signal ('Use when...') and then delivers the resource, metrics, source, example, and price in a compact set of sentences. It is longer than strictly necessary, but each sentence adds a distinct piece of decision-relevant information.

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?

Given there is no output schema, the description explains the return contents (frequency, losses, deaths, trend direction) and even illustrates magnitudes with the Texas example. It could be more precise about output shape or the meaning of trend direction, but it is adequate for a simple two-parameter read-only tool.

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?

With schema coverage at 50%, the description compensates by giving a concrete 'Texas 10-year history' example that demonstrates the state and years_back parameters in action. It doesn't document bounds or edge cases, but the example meaningfully clarifies how the two inputs behave.

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 returns NOAA's official tally of billion-dollar weather disasters with specific metrics and disaster types, giving agents a concrete sense of the resource and output. However, it does not explicitly distinguish itself from overlapping siblings like get_noaa_disaster_economics or get_climate_risk_benchmark, so it stops short of full sibling differentiation.

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?

It opens with explicit use cases (insurance underwriting, real estate due diligence, ESG disclosures, board briefings), telling agents when to reach for this tool. It lacks any when-not-to-use guidance or named alternatives, so it earns a 4 rather than a 5.

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