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

With no annotations provided, the description carries the full disclosure burden. It states the tool is read-only, anonymous, free, counts service calls rather than unique agents, and does no tracking. This gives an agent a clear safety and semantics profile.

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 concise yet complete, front-loading the purpose and then adding behavioral context, an alternative, and an example. Each sentence adds value without 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?

For a simple, parameterless, read-only counter, the description covers what it counts, what it does not count, privacy/safety characteristics, invocation requirements, and the relevant alternative. No critical information 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?

There are zero parameters, and the description explicitly reinforces this: 'no parameters — call with {}.' This exceeds the baseline for parameterless tools by removing any ambiguity about invocation.

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's function: a counter for agents helped, clinic diagnoses, and tool uses served. It also explicitly distinguishes itself from qm_clinic_stats, so an agent can tell them apart without inspecting schemas.

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?

It says exactly when to use this tool and names the alternative: 'use qm_clinic_stats instead for condition-level breakdowns.' It also instructs the agent to call with no arguments and {}.

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