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

With no annotations, the description carries the full disclosure burden. It usefully names the upstream source (Census Bureau), implying data provenance and vintage, and it enumerates what comes back. But it says nothing about accuracy limits, permissions/API keys, rate limits, or what happens when an address cannot be matched.

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?

A single front-loaded sentence with a clear verb-resource-return structure and no filler. It loses a point because the majority of the sentence enumerates return fields that the existing output schema already documents.

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?

An output schema exists, so the long list of returned fields is largely redundant work, while the gaps that matter — accepted input address format, US-only input restriction, and no-match behavior — go unaddressed. Adequate to call correctly in the happy path, thin on the edges an agent will hit.

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?

Schema coverage is 0% for the single required 'address' parameter, so the description must compensate. 'Match a US street address' does hint that the input is one free-form US address string rather than components, but it gives no format example, no handling of unit/apt suffixes, and no guidance on whether the input or output is the standardized form.

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 gives a specific verb ('Match') plus a specific resource ('US street address') and names the data source ('Census Bureau geocoder'), so an agent knows exactly what it does. The 'US' qualifier implicitly separates it from the generic 'geocode' sibling, but the sibling is never named, so differentiation is inferred rather than stated.

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?

There is no explicit when-to-use guidance and no named alternative — the description never tells the agent to prefer this over 'geocode' or 'postal_code'. The only usable signal is the implicit 'US' scope, which an agent must infer rather than read.

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