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

With readOnlyHint=true already provided by annotations, the description adds valuable behavioral context beyond that: the return fields, the geographic coverage (3,222 counties), the data source (USDA normalization), and the update cadence ('Updates: on source cadence'). No contradictions with 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 concise and front-loaded with the core action and return type. It packs essential information (scope, fields, normalization source, usage triggers, update cadence) into two sentences without filler or redundancy.

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 lookup tool with one optional parameter, the description is highly complete: it lists return fields, usage scenarios, data provenance, and update frequency. The optional parameter is fully explained in the schema, and no output schema is needed since the description enumerates the returned fields.

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 only parameter, 'days', is fully documented in the input schema with a description covering its purpose, range, and tier requirement. The tool description itself adds no additional parameter semantics beyond the schema, so the baseline score of 3 for high schema coverage 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 clearly states the tool returns a 0-100 agricultural-production significance score for US counties, including specific fields (score, national_percentile, state_rank, top_drivers, as_of, methodology_version) and the normalization source (USDA county-level statistics). This is a specific verb+resource with clear scope, making it easy to distinguish from the many sibling 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 explicitly lists when to call the tool: 'when the user asks about local farm output, crop or livestock concentration, or which counties lead US agricultural production, or when timing ag lending, equipment or facility siting, and rural supply-chain decisions.' This provides clear user-intent triggers, though it does not name alternative tools or explicitly state when not to use it.

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