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

With no annotations at all, the description carries the full burden, and it does disclose meaningful behavior: every figure includes the underlying sample size, an uncertainty range, and a flag for small samples. It also states credential requirements (none), cost (free), and legal source. It stops short of describing caching, pagination, or scope limits, but this is solid disclosure for an annotation-free tool.

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?

Front-loaded with the question the tool answers, followed by the metric list and then the statistical caveats, with no wasted clauses. The lead sentence is phrased in first-person agent voice rather than tool voice, which is slightly awkward but still efficient.

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 must convey the return shape, and it does: metrics with counts, uncertainty ranges, and small-sample flags. Credential, cost, and legal source are also covered. No material gap remains for an agent deciding whether to call it, though scope (which courts/cases) is unstated.

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 takes zero parameters, so the baseline is 4. The description correctly adds no parameter detail and instead spends its text on what the returned figures contain, which is the right allocation for a parameterless tool.

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 concretely what the tool produces: decision times, order-compliance rates, and appeal rates for decided cases. It is far more specific than a tautology, but it never distinguishes itself from a plausible sibling like bench_certification_rates, so an agent has to guess which statistics tool is the right one.

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?

Usage is implied through the framing question ('how quickly cases are decided and whether agents follow the orders'), which signals the scenario in which the agent would want this. However, there is no explicit when-to-use/when-not guidance and no named alternative among the many sibling statistics/reporting tools.

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