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

Annotations already declare readOnlyHint=true and openWorldHint=false. The description adds valuable context beyond this: it specifies the update cadence ('Updates: daily'), the data sources (USGS/NOAA), and the output schema details (field names). This gives the agent confidence in data freshness and composition, beyond the annotation flags.

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 three concise sentences: what it returns, when to call it, and how often it updates. No filler or redundancy, every sentence 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 tool with one optional parameter and no output schema, the description is complete: it explains the output fields, underlying data sources, update frequency, and appropriate use cases. The only omitted details (history series) are fully covered in the schema, so no critical gap exists.

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 input schema provides 100% coverage for the single optional 'days' parameter, explaining its purpose, constraints, and tier requirement. The description does not repeat or add parameter-specific information, so the baseline of 3 applies.

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 opens with a specific verb 'Returns' and clearly defines the tool's output as a '0-100 agricultural water-stress read' with methodology and field names, distinguishing it from generic data tools. It also lists concrete output fields, making the purpose unambiguous.

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 'Call when the user asks about drought, irrigation stress, aquifer depletion, or heat-driven crop risk, or when timing grain hedges, irrigation capex, or crop-insurance reviews', providing clear trigger conditions. It does not mention exclusions or alternatives among the many siblings, 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.