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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds what to expect: event count, total losses, deaths, and historical context with 10-year trend acceleration, plus a concrete example. This is useful behavioral detail beyond the annotations.

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 well-organized and front-loaded with the key use cases, then the data returned, a concrete example, and authoritative citations. Every sentence adds value, with no redundancy or fluff, making it appropriately sized for a specialized financial tool.

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 simple tool with one optional parameter and no output schema, the description gives enough context to understand the tool's purpose, data content, and a realistic example. The only notable gap is explicit parameter semantics, but the overall picture is fairly 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?

The schema has one parameter 'year' with no description (0% schema coverage). The description does not explicitly explain the year parameter; it only shows an example using 2023, implicitly suggesting year is an input. It does not clarify allowed values, default behavior, or format, so the description fails to compensate for the absent schema documentation.

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 uses a specific verb ('Returns') and resource ('NOAA's official annual billion-dollar disaster economics'), clearly stating the tool's output. It distinguishes from siblings by focusing on macroeconomic loss data (event count, total losses, deaths) rather than event-level or risk-score data, and the use cases reinforce its unique role.

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 explicitly states 'Use when establishing the macroeconomic cost of climate risk' and lists concrete scenarios (ESG reporting, reinsurance, SEC/TCFD disclosures). It provides strong contextual guidance but does not mention when not to use the tool or name alternatives, so it stops short of a 5.

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