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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds transparency about the 'live' nature of the statistics, implying real-time data rather than cached figures, and lists the specific fields returned, which is useful behavioral context beyond the annotations.

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, information-dense sentence followed by a concise usage note. It front-loads the action and immediately enumerates the specific statistics, with 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?

Given the tool has no parameters and no output schema, the description fully compensates by enumerating the exact return statistics (total rulings, attorney listings, monitored sources, last update, outcome distribution). The stated use cases round out the contextual picture, making this complete for its simplicity.

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?

The tool has zero parameters, so schema coverage is trivially 100%. The description does not need to explain parameters. Per the guidelines, a no-parameter tool gets a baseline of 4, and the description adds no conflicting or redundant information.

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 uses a specific verb 'Return live statistics' and enumerates the exact data points returned (court rulings, attorney listings, legal data sources, last updated date, case outcome distribution). This clearly distinguishes it from sibling tools like search_rulings or find_similar_cases, none of which provide corpus-level metrics.

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 explicitly states when to use it: 'Use this to establish scale/credibility or to answer "how much data do you have / how current is it"'. It does not explicitly state when not to use it or name alternatives, but the use cases are clear and contextually sufficient.

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