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vmware-knight

deploy_vm_from_template

Deploy a new VM from a vSphere template, with optional CPU, memory, datastore, snapshot, and power-on settings. Requires an existing template; use vm_clone for running source VMs.

Instructions

[WRITE] Deploy a new VM by cloning from a vSphere template.

Returns a status string. Use for VMs marked as templates; for a running source VM use vm_clone. Requires an existing template — convert_vm_to_template makes one.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cpuNoOverride CPU count (optional).
targetNoOptional vCenter/ESXi target from config.
new_nameYesName for the new VM.
power_onNoPower on after deployment.
memory_mbNoOverride memory in MB (optional).
snapshot_nameNoSnapshot the new VM with this name.
template_nameYesSource vSphere template name.
datastore_nameNoTarget datastore (template's own if omitted).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.12.10

TDQS

A4.5/5.0
Behavior4/5

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

The [WRITE] prefix reinforces that this is a mutating operation, consistent with readOnlyHint=false. The description adds value by stating that a return status string is produced and by disclosing the prerequisite that an existing template is required. It does not dwell on safety since destructiveHint=false, so a 4 is appropriate.

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?

Every sentence in the description earns its place: purpose, return value, correct use case, and prerequisite. It is compact, front-loaded, and avoids restating schema fields or annotations.

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?

Given the output schema exists, annotations are present, and all parameters are already described in the schema, the description covers the remaining contextual needs: when to use it, what it returns, and what must exist beforehand. Nothing essential is missing for an agent to invoke it correctly.

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

Parameters3/5

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

Schema description coverage is 100%, so the input schema already documents all eight parameters and their meanings. The description adds no parameter-specific detail beyond the prerequisite relationship to template_name, so the baseline score of 3 is correct.

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 states a specific action and resource: 'Deploy a new VM by cloning from a vSphere template.' It also distinguishes itself from vm_clone by explicitly saying it is for VMs marked as templates, not running source VMs. This is enough for an agent to separate it from the relevant siblings.

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

Usage Guidelines5/5

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

The description gives explicit usage conditions: use for templates, use vm_clone for a running source VM, and require an existing template, with convert_vm_to_template named as the way to create one. This is clear, actionable routing guidance that leaves little to inference.

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