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

Annotations already cover safety (readOnlyHint, idempotentHint, openWorldHint=false). The description adds real context beyond them: no API key required, no cost, 25-row default truncation, and the caveat that the CMS Medicare labor market area is a different geography sharing the same code space.

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?

Front-loaded with the resource and its scope caveat, and every clause carries information. The single dense paragraph packs several distinct concepts together, which slightly hurts scannability but nothing is wasted.

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?

Covers scope, defaults, truncation behavior, cost/auth, geographic caveats, and the kind of attributes returned (divisions, combined area, land area, delivery footprint). With no output schema, this is sufficient for an agent to call it correctly.

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 100%, so the baseline is 3; the description goes further by framing why the state filter works the way it does (an area spans several states, so it matches the whole state list) and by tying the unfiltered default to a concrete example (Aberdeen).

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?

Names a specific resource (US metropolitan and micropolitan statistical areas / CBSAs) with the distinguishing fact that only 393 of 935 are metropolitan. This clearly separates it from siblings like county_reference and zip_lookup.

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?

Gives explicit operational guidance: filter by state to get every area in that state, and warns that an unfiltered call returns only the first 25 alphabetically. It also warns not to treat a CBSA count as a metro count. It stops short of naming an alternative sibling tool for related lookups.

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