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

Annotations already cover read-only/idempotent/closed-world, so the safety profile is handled. The description still adds real value by enumerating what the response contains (queued + warming + running, disk free_gb/below_target/below_floor/refusing_jobs) and defining the 'degraded' status condition, plus noting the Android emulator is off so warming jobs no longer imply a warm-up delay.

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-loads the core purpose and keeps the payload enumeration tight. The closing 'Android emulator is now OFF' note is a bit of a changelog aside that doesn't directly help an agent decide or call, but it is short and defensible context.

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?

No output schema exists, so the description carries the burden of describing returns — and it does reasonably well, listing queue composition, disk fields, and the degraded threshold. It omits any reachability field/boolean and error-signalling behavior, which are small but real gaps for a health-check tool.

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, which is the baseline-4 case. The field names listed (disk sub-fields, status) describe the response rather than inputs, so there is nothing further for the description to add on parameter semantics.

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?

Names a specific action (health check of the Flow generation backend) plus the exact payload it inspects — queue depth and disk state. It does not, however, differentiate itself from close siblings like flow_status, flow_dashboard, or check_job, which an agent could easily confuse it with.

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?

There is no explicit when-to-use guidance, no preconditions, and no mention of flow_status/flow_dashboard/check_job as alternatives. Use is only inferable from the word 'check', which is the same situation as the MID calibration example that scored 2.

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