review_stats

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

No annotations are provided, so the description carries the full burden. It lists all returned statistics (total entries, per-axis counts, versions), which is good, but it does not disclose whether the operation is read-only, requires authentication, or has any side effects. The behavior is well-described in terms of output, but missing traits like idempotency.

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, concise sentence that efficiently lists all key statistics without any unnecessary words. Every element earns its place.

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 zero parameters and no output schema, the description is mostly complete. It lists the types of statistics returned. However, it could clarify that the output is a single object or provide a hint about the data structure, which would make it fully self-sufficient.

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 input schema has zero parameters and 100% schema description coverage. The description adds value by detailing the statistics available, though parameter semantics are not applicable. Baseline for 0 params is 4, and the description meets that.

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 it provides 'coverage statistics' and lists specific counts and versions, distinguishing it from sibling tools like differential_diagnosis or list_axes. The verb 'statistics' plus the detailed list of items makes the purpose unambiguous.

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 implies use when coverage statistics are needed, but it does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives among siblings. The context is clear but lacks exclusionary guidance.

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