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

Annotations already cover readOnly, idempotent, and openWorld=false, so the bar is lower. The description adds genuinely useful context beyond them: it is free, requires no API key, and returns rules plus counts plus a worked example.

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 tight sentences: what it is, the key nuance (invalid alternates), and the concrete SHAMONG example. The example earns its place by making the concept unambiguous, and the return/cost facts are front-loaded appropriately.

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?

With no input params and no output schema, the description must explain what comes back, and it does (rules, counts, worked example). The only small gap is that it doesn't indicate the response format (structured vs prose), which an agent might want to know.

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 tool takes zero parameters, so the schema carries no semantics to explain and the baseline is 4. The description correctly avoids inventing parameter behavior.

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?

States a specific subject (how USPS names a ZIP Code and which names are valid for mail) and what it returns (rules, counts, worked example). It is clearly a rules/reference tool rather than a data lookup like zip_lookup or zip_facts, though the differentiation from those siblings is left implicit rather than named.

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 implies the use case (deciding whether a city name is mailable, e.g. SHAMONG vs SHAMONG TOWNSHIP) but never states when to call this versus zip_lookup, validate_address, or zip_facts, and gives no exclusions.

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