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

The readOnlyHint annotation already signals a safe read; the description adds useful context by explaining the score is a composite of 9 layers and notes 'Updates: on source cadence.' This goes beyond annotation-only information and aligns with the read-only nature.

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?

Three sentences: return value/scope, usage triggers, and update cadence. Front-loaded and every sentence adds distinct information.

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?

The description indicates what is returned (composite score, component scores, drivers, coverage), when to use it, and update cadence. It lacks an output schema but gives enough for an agent to select and invoke it; not fully detailing county selection semantics is a minor gap.

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 schema (optional history series up to 1825 days, Gold tier requirement). The description adds no additional parameter detail, but the schema coverage is 100%, so the baseline 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 defines the resource as a '0-100 community quality-of-life composite' for US counties, including component_scores, named drivers, and layer coverage. It also scopes the data to '9 AlpineDataWorks V2 county layers joined on county_fips,' giving enough specificity to distinguish it 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?

It provides explicit call scenarios: 'Call when the user asks what it's like to live in a place or compares counties for relocation or hiring, or when timing site-selection, expansion, or community-investment decisions...' This covers when the tool should be selected, though it does not name alternative tools or 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.