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AIops-tools

queue-aiops

delete_policy

Delete a RabbitMQ policy with a recorded undo to re-create it exactly. Preview with dry_run before applying.

Instructions

[WRITE][risk=medium] Delete a rabbitmq policy; the undo re-creates it.

Reads the policy first so the recorded undo can re-create it exactly. Pass dry_run=True to preview.

Args: vhost: The policy's vhost (the default vhost is '/'). name: Policy name (from list_policies). dry_run: If True, preview without deleting. target: rabbitmq target name from config; omit for the default.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
vhostYes
targetNo
dry_runNo
Behavior5/5

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

No annotations are provided, so the description carries the full burden. It opens with [WRITE][risk=medium], explicitly discloses the read-first behavior for undo, and explains the dry_run parameter. This provides strong safety and reversibility context beyond what the schema shows.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the essential purpose and risk, followed by a single explanatory sentence and a clean Args list. There is no fluff or redundancy; every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite lacking annotations and an output schema, the description covers the tool's purpose, undo mechanics, dry-run behavior, and all parameters. This is fully sufficient for an agent to select and invoke the tool correctly, especially with sibling tools like undo_list and list_policies in context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description compensates thoroughly: it gives vhost's default, notes that name should come from list_policies, explains dry_run as a preview, and identifies target as the rabbitmq config name. Each parameter gets meaningful context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Delete') with a clear resource ('a rabbitmq policy') and notes the undo behavior, distinguishing it from siblings like set_policy and delete_queue. The phrase 'the undo re-creates it' adds a unique functional trait.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It clearly implies when to use the tool (to delete a policy) and even provides a dry-run option for preview before committing. It references list_policies for obtaining names, but does not explicitly state when not to use it or compare to alternatives explicitly, so it stops short of a 5.

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

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