VMware-AIops

vm_revert_snapshot

Destructive

Revert a virtual machine to a specific snapshot, discarding all changes made after the snapshot was taken.

Instructions

[WRITE] Revert a VM to a named snapshot (loses changes since snapshot).

Args: vm_name: VM to revert. snapshot_name: Snapshot to revert to. target: vCenter/ESXi target name from config.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "vm_name": "<vm_name>",
      "snapshot_name": "<snapshot_name>"
    },
    "name": "vm_revert_snapshot"
  }
}

Input Schema

Name	Required	Description	Default
`target`	No
`vm_name`	Yes
`snapshot_name`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Addedv1.5.29May 29, 2026

TDQS

A4.2/5.0

Behavior4/5

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

The description explicitly mentions 'loses changes since snapshot', which directly aligns with the destructiveHint annotation and adds context beyond it. It also implies non-idempotency. No side effects like power state requirements are mentioned, but the core destructive behavior is well-disclosed.

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 extremely concise and well-structured: a [WRITE] prefix, a single sentence stating the action and effect, followed by a clear Args list. Every sentence is informative; no wasted words.

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

Completeness4/5

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

For a simple revert tool with 3 parameters, the description covers purpose, effect, and parameter meanings. An output schema exists but is not needed in the description. Potential missing details include prerequisites (e.g., VM and snapshot existence) and error conditions, but overall the description is adequate for selecting and using the tool.

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

Parameters4/5

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

With 0% schema coverage, the description compensates by listing and explaining each parameter: vm_name, snapshot_name, and target. The target is described as a vCenter/ESXi target name from config, adding real-world context not present in the schema. However, the explanations are minimal and could be more detailed.

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 clearly states the action: reverting a VM to a named snapshot, with a specific verb ('Revert') and resource ('VM'). The warning 'loses changes since snapshot' distinguishes it from non-destructive snapshot operations like listing or creating snapshots, and fits well among sibling tools.

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

Usage Guidelines3/5

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

The description does not explicitly state when to use this tool versus alternatives such as vm_create_snapshot or vm_delete_snapshot. While the destructive hint suggests careful use, no guidance on prerequisites or scenarios to avoid is provided, leaving the agent to infer context.

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