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

Annotations already cover read-only, idempotent, non-destructive, closed-world behavior, so the bar is lower. The description adds genuinely useful context beyond them: the exact informational payload (deadline, dismissal rate, best reason, help resources) and the 'Not legal advice' disclaimer, which tells the agent how to frame the response. It stops short of saying whether rates are aggregate estimates or jurisdiction-wide.

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 dense sentence that front-loads the audience and then lists the four outputs in the order the agent will use them, followed by a short scope disclaimer. No filler.

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 output schema, the description does the necessary work of enumerating what comes back, and the one parameter is fully specified by the schema. Minor gap: it does not indicate that the guidance is based on aggregate historical data rather than the specific citation's facts, which affects how the agent should present it.

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?

With a single required parameter at 100% schema description coverage and a fully enumerated value set, the schema carries the semantics. The description only loosely corroborates it by scoping to 'parking or camera' tickets, matching the enum's red_light/speed_camera entries; it adds no new meaning about how violation_type drives the answer.

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 resource (Chicago parking or camera ticket) and enumerates exactly what the agent gets back: deadline, dismissal frequency, the winning reason, and where to get help contesting. It is clearly distinct from schedule/lookup siblings, though it never explicitly names ticket_win_rate, which overlaps with the 'how often dismissed' output.

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 audience framing ('for someone holding a Chicago parking or camera ticket') implies when to call it, and 'Not legal advice' sets a boundary. But there is no explicit when-not guidance and no routing to or from ticket_win_rate, which appears to return a subset of this data.

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