qm_clinic_stats

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

With no annotations provided, the description carries the full burden, and it does so thoroughly: anonymous, aggregate, free, no individual records, and a suppression threshold for conditions with fewer than 10 occurrences. This is unusually transparent about privacy and data-shaping behavior.

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 front-loaded with the core definition and threshold, then provides usage context and an alternative. The final example sentence is slightly redundant with the opening definition and the 'call with {}' instruction, but overall the structure is tight and readable.

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 no-parameter, no-output-schema tool, the description covers what data is returned, privacy constraints, when to use it, and how it relates to a sibling tool. Nothing essential for correct invocation is missing.

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, and the description explicitly confirms this with 'no parameters — call with {}'. This fully addresses invocation semantics and exceeds the baseline for a no-parameter 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?

States specifically that it provides anonymous aggregate clinic statistics: total serves and condition counts. It also distinguishes itself from qm_clinic_diagnose by noting it carries no individual records, so an agent can select it correctly.

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?

Explicitly tells when to use it (gauging swarm-level patterns before deeper checks), when not to use it (for specific agents), and names the alternative tool (qm_clinic_diagnose). It also says to call with no arguments or {}, leaving no ambiguity about invocation.

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