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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint=false, so safety needs no restating. The description adds genuinely new context: the data provenance (City hearing records obtained under Illinois FOIA) and the scope restriction that the rate only covers tickets contested by mail, which materially affects interpretation. It does not mention sample sizes or staleness of the records, which keeps it off a 5.

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 sentences, zero filler. The definition of the metric comes first and the parameter handling comes second, so an agent reading only the opening clause still knows what it gets.

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 single-optional-parameter read tool with no output schema, the description covers what is measured, where the data comes from, and how the response changes when the parameter is omitted. What is missing is any hint about the shape or reliability of the returned rate (e.g. whether low-volume types are reported, or whether counts accompany the percentage).

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 enum enumerates all violation types, so the baseline is 3. The description earns above baseline by explaining the semantics of omitting the sole optional parameter — the response changes shape to an overall rate plus a list of types, which the schema does not convey.

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-and-resource combination: how often Chicago parking/camera tickets 'of a given type are dismissed when contested by mail.' The 'contested by mail' qualifier makes the measured population precise, which is more than most descriptions do. It does not explicitly contrast itself with the sibling should_i_contest, so it stops short of a 5.

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 only usage guidance is parameter-level: 'Omit violation_type for the overall rate and the list of types.' That is helpful invocation guidance but not tool-selection guidance. Nothing tells the agent when to consult this rate table versus calling should_i_contest, or that should_i_contest is the decision-oriented sibling.

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