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

Annotations already cover read-only, idempotent, non-destructive, closed-world behavior. The description adds meaningful domain context: only active licenses are counted, and results include the list's last-read date and publishing agency, which is important for trusting freshness.

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 zero filler. It conveys scope, grouping, and returned metadata without 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 one-parameter, read-only tool, the description is nearly complete: it explains what is counted, how it is grouped, and two important returned metadata fields. With no output schema, it could say slightly more about the shape of the returned counts, but the essentials are present.

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% and the single state parameter is fully documented in the schema. The description adds only that the state corresponds to 'one state's list,' but no additional format or validation detail beyond the schema's two-letter code pattern.

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 verb and resource: counting active cannabis licenses on one state's list, broken out by license type. This clearly distinguishes it from lookup_license and licensed_near in practice, though it never names a sibling tool explicitly.

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 use case is strongly implied by 'one state's list, by license type,' but there is no explicit 'use this when' or 'use X instead' guidance relative to state_license_report or lookup_license.

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