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

Annotations already establish this as a safe, idempotent, closed-world read. The description goes further by disclosing data provenance (public sources) and a coverage boundary ('all states the site tracks'), which helps the agent calibrate expectations for completeness.

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?

Two tight sentences: the scope statement is front-loaded and the calling instruction follows immediately. No filler or redundancy.

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-optional-parameter read tool with full annotation coverage and no output schema, the description supplies scope, source type, and coverage limits. It stops short of hinting at the shape of returned results, but nothing essential to invocation is missing.

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 description coverage is 100% and the single optional parameter is fully documented there. The description only restates the accepted formats and optionality, adding no format or semantics beyond the schema, so the baseline of 3 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 states a specific verb (state) and resource (bans, scheduling and rules on concentrated 7-OH and kratom alkaloids), giving an agent a clear picture of what it returns. It does not explicitly distinguish itself from policy-adjacent siblings like bill_status or nc_legislation, which also concern drug legislation.

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 tells the agent how to scope the call (pass a state, or omit for all tracked states), which is useful operational context. However, it offers no guidance on when to prefer this over bill_status or nc_legislation, so alternative selection is left to inference.

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