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

Annotations already mark readOnlyHint=true, and the description is consistent with that. It adds useful behavioral context beyond the annotations: the update cadence ('on source cadence'), the county-level aggregation, and the specific output fields. It does not discuss the Gold-tier history behavior, but that is covered in the parameter schema.

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 long, front-loads the core return value and scope, then gives practical usage triggers and a brief update note. Every sentence earns its place with no filler or repetition.

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, the description covers the purpose, use cases, output fields, and refresh cadence. The main gap is that it does not clarify whether the tool returns data for all counties or requires a county selector, since the schema has no county parameter; the mention of 'county_fips' in the output partially mitigates this.

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 covers the only parameter (days) with 100% coverage, including range, behavior, and tier fallback. The description itself adds no parameter-level detail, which is acceptable per baseline. However, the description's phrase 'for any of 3,222 US counties' is not matched by a county parameter in the schema, leaving the selection mechanism ambiguous.

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'), names the exact deliverable ('0-100 data-center capacity-concentration score'), defines the geographic scope ('3,222 US counties'), the aggregation grain, and the output fields. This clearly distinguishes the tool from the many sibling county-level data tools in the catalog.

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 provides explicit trigger scenarios: 'Call when the user asks about data-center density, where compute or AI infrastructure is concentrated, or colocation markets, or when timing site selection, fiber buildout, or grid-capacity planning decisions.' It does not mention exclusions or name alternative tools, 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.