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

The description is fully transparent, detailing the data source, record count, time range, and aggregation capabilities. It includes example outputs and grouping options. Annotations already mark it as read-only, idempotent, and non-destructive, and the description adds rich behavioral context without contradiction.

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?

The description is a single coherent paragraph with example queries and use cases. It is front-loaded with the main purpose. Some redundancy exists (e.g., repeating 'convictions'), but overall it is well-structured and not overly verbose.

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?

Given 7 parameters, no output schema, and the tool's complexity, the description adequately covers what the tool does, its source, and how to use it. It provides example queries and grouping options. It does not detail the return format, but the examples imply counts, so it is mostly complete.

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?

All 7 parameters are fully described in the input schema (100% coverage). The description adds a general usage pattern ('group by violation or disposition, narrow with date range') but does not provide additional meaning beyond what the schema already offers. Baseline of 3 is appropriate.

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 clearly states the tool counts Washington DC traffic convictions by violation and court disposition, using a specific dataset (DMV conviction file) with concrete examples. It differentiates from sibling tools like dc_dmv_offices and dc_dmv_vehicle_inspections which serve different purposes.

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 provides explicit example queries (e.g., 'most common traffic violations', 'how many DUI convictions') and mentions grouping and date range filtering. It does not explicitly state when not to use it or name alternatives, but the context is sufficiently clear for an agent.

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