aetre_heterogeneous_queues

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

With no annotations provided, the description carries the full burden of behavioral disclosure, but it only says 'evaluates' and 'generating actions' without clarifying whether it mutates state, requires any special permissions, or is purely analytical. This is a significant gap for a tool that appears to be a simulation/analysis utility.

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 a single, front-loaded sentence that efficiently captures the core purpose and expected outputs. There is no wordiness, and every phrase contributes to the agent's understanding of the tool's function.

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?

The description lacks crucial details: there is no mention of what the output looks like, the necessity of the api_key, the meaning of 'bottleneck domains' or 'capacity rebalancing actions', or how the network is modeled. For a tool with no output schema, the description is too thin to fully guide an agent.

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 100% for the top-level fields (pools and api_key), and the description adds no extra meaning about how parameters like arrival_rate or service_rate relate to the evaluation. The baseline of 3 is appropriate since the schema documents the parameters adequately, though the description could have added context on their role in bottleneck identification.

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 evaluates a multi-specialist heterogeneous reviewer network, identifies bottleneck domains, and generates capacity rebalancing actions. It gives a specific verb ('Evaluates'), a resource ('multi-specialist heterogeneous reviewer network'), and concrete outputs, making it distinct from siblings like aetre_congestion_matching or aetre_system_catalog.

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?

No guidance is given on when to use this tool versus alternatives. It does not state any conditions, prerequisites, or alternatives, leaving the agent to infer usage from the name and description alone.

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