rabbitmq_queue_backlog_rca

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

With no annotations, the description carries the full burden and does well: it declares '[READ]' semantics, describes the classification logic (no consumers, unacked pileup, rate mismatch, residual), mentions global memory/disk alarm detection, and notes that 'every finding carries its numbers.' It doesn't cover error handling or permissions, but the read-only nature and analysis behavior are transparent.

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 well-structured: a concise summary sentence, a clarifying paragraph, and a bulleted 'Args' list. There is no redundancy; every sentence contributes essential information about behavior, usage, or parameters.

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 tool with no output schema and no annotations, this description is surprisingly complete. It explains the return dict structure, the operational modes, and the classification causes. Minor gaps like threshold configuration or error scenarios are not mentioned, but overall the context is sufficient.

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%, but the description's 'Args' section fully compensates by explaining each parameter: vhost (restrict live pull), top (row count), queues (injected rows), nodes (node health rows), target (RabbitMQ target name). This adds crucial meaning beyond the bare schema names.

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 opens with a specific verb+resource+output: 'Rank backlogged queues and map each to a cause + action.' It lists explicit cause categories and mentions flagging queues over a threshold, clearly distinguishing this from sibling tools like list_queues or node_health.

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 description explains how to invoke it in different modes ('Pass queues (and optionally nodes) for pure analysis, or a target to pull live') and mentions vhost/target optionality. It does not explicitly contrast with alternatives or state when not to use it, but the usage context is clear.

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