queue_sizing

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

Annotations already declare readOnly, idempotent, closed-world and non-destructive, so the safety profile is covered structurally. The description adds a genuine constraint beyond the schema surface: a hard ceiling of 100,000 total concurrent slots (consumers × concurrency), which is exactly the kind of operational limit an agent needs before calling.

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 dense sentences with the analytic method and computed outputs front-loaded, then the hard constraint. Nothing is wasted, though the second sentence's parenthetical formula is the only piece of parameter-level detail present.

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?

An output schema exists so return values need not be described, and the safety profile comes from annotations. What is missing for a six-input quantitative model is any account of input units/relationships, the meaning of 'stable' Erlang C assumptions, or how defaults (70% target utilization, concurrency 1) affect results.

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% across six required parameters, so the description must carry the burden and largely does not. It names outputs (utilization, wait probability, drain time, target consumers) rather than explaining inputs like arrivalsPerSecond, serviceTimeMs, or backlogMessages; only the 'consumers × concurrency' phrasing indirectly clarifies maxConcurrencyPerConsumer 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?

States a specific verb ('size') and resource ('consumers') plus the analytical basis (Little's law, Erlang C), which is far more informative than a generic 'calculate' description. It does not explicitly differentiate itself from nearby siblings like capacity_plan or latency_budget, which also deal with sizing math.

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?

Usage is only implied: the mention of Little's law / Erlang C signals a queueing-model calculator, so an agent can infer it applies to consumer-throughput sizing. There is no explicit statement of when to prefer this over capacity_plan or latency_budget, and no prerequisites or exclusions are given.

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