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

Annotations already declare readOnlyHint=true. The description adds non-obvious context: coverage of all US counties, federal data source, output fields, and update cadence. It doesn't cover rate limits or pagination, but for a read-only bulk lookup tool this is adequate and goes 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 three sentences with no filler. It front-loads the core purpose, then provides use-case guidance and update cadence. The first sentence is dense but every element earns its place by listing concrete output fields and data inputs.

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?

Despite lacking an output schema, the description enumerates the key return fields and the exact geographic scope. It also tells the agent when to call the tool and how fresh the data is. For a simple read-only tool with one optional parameter, this is fully 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 description covers 100% of the single optional parameter (`days`) with clear, detailed semantics. The tool description adds no additional param-level meaning, 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 and resource: 'Returns a 0-100 healthy-food access score for all 3,222 US counties.' It also enumerates the data components and output fields, making the tool's purpose unmistakable. Even though sibling names are opaque numeric identifiers, the description itself clearly differentiates this as a food-access scoring tool.

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?

Provides explicit call triggers: 'Call when the user asks about food deserts, grocery access, food insecurity geography, or nutrition equity, or when timing food-program siting, retail expansion, or grant targeting.' This is strong contextual guidance, but it does not mention when not to use the tool or name specific 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.