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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds context about the data source (NOAA NCEI) and authority, but does not disclose potential limitations or behavioral nuances beyond what annotations imply. The added value is moderate, not rich.

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 usage and purpose, includes a useful example and source. The 'cited by' sentence adds credibility but is not strictly necessary for tool invocation, making it slightly less concise than ideal.

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 no output schema, the description sufficiently explains return contents (frequency, losses, deaths, trend direction) and provides an example. It covers usage, output, and source but lacks explicit parameter details and potential 'when-not-to-use' guidance, which would make it more 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 50%; state is described but years_back is not. The example ('Texas 10-year history') indirectly implies how parameters map, but the description never explicitly explains years_back. It adds some meaning beyond the schema but does not fully compensate for the gap.

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 what the tool returns: 'NOAA's official tally of billion-dollar weather disasters' with specific outputs (frequency, losses, deaths, trend). However, it does not explicitly distinguish itself from sibling tools like get_noaa_disaster_economics, so it lacks explicit 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?

The opening sentence gives explicit use cases: 'insurance underwriting, real estate acquisition due diligence, ESG climate risk disclosures, or board-level climate briefings.' It provides clear context but does not mention when not to use it or name alternatives, so it misses the top score.

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