user_count

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

Annotations already declare readOnlyHint=true, so the '[READ]' tag is largely redundant. The description does add useful cost context ('cheap'), but it omits return format, behavior on unknown target, and any auth/rate considerations. With annotations carrying the safety profile, this modest addition justifies a 3.

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?

Two tight lines with the core purpose front-loaded and an explicit Args section for the single parameter. No wasted prose, though the '[READ]' tag duplicates the annotation.

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 trivial single-optional-param count tool with no output schema, the description covers purpose and the one parameter's semantics adequately. It stops short of explaining the count's scope nuances (e.g., active vs total) but the base need is met.

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?

Schema description coverage is 0%, so the description must compensate, and it does: it explains 'target' is an IdP target name from config and that omitting it yields the default. That resolves both the parameter's meaning and its default semantics beyond what the bare schema reveals.

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 a specific verb+resource ('total user count in the realm') and tags it '[READ]', making it clearly distinct from enumeration siblings like list_users and user_detail. An agent can tell this is a scalar count query, not a listing, without opening the schema.

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 parenthetical 'the cheap health probe' implies when this tool is appropriate (lightweight checks over full listings), but it never names an alternative or states explicit when/when-not conditions versus list_users. Usage is implied rather than spelled out.

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