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vm_create_plan

Creates a validated execution plan for multi-step VM operations, including rollback information and step-by-step actions. Use to preview and confirm complex VM workflows before applying them.

Instructions

[WRITE] Create an execution plan for multi-step VM operations.

Auto-triggered when operations involve 2+ steps or 2+ VMs. Validates actions, checks target existence in vSphere, and generates a plan with rollback info for each step.

Each operation is a dict with "action" key plus action-specific params. Allowed actions: power_on, power_off, reset, suspend, create_vm, delete_vm, reconfigure, create_snapshot, delete_snapshot, revert_snapshot, clone, migrate, deploy_ova, deploy_template, linked_clone, attach_iso, convert_to_template.

Example: operations=[ {"action": "power_off", "vm_name": "test-1"}, {"action": "revert_snapshot", "vm_name": "test-1", "snapshot_name": "baseline"}, {"action": "power_on", "vm_name": "test-1"} ]

Returns plan dict with plan_id, steps, summary (vms_affected, irreversible_steps, rollback_available). Show to user for confirmation before calling vm_apply_plan.

Args: operations: List of operation dicts, each with "action" + params. target: Optional vCenter/ESXi target name from config.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
operationsYes
targetNo
Behavior5/5

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

Description discloses write nature ([WRITE]), validation/checks, generation of rollback info, and non-destructive behavior (returns plan). Adds value beyond annotations which only give basic hints. No contradiction.

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?

Well-structured with front-loaded purpose, then triggers, behavior, allowed actions, example, return format, usage guidance. Efficient use of sentences without redundancy.

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 no output schema, description details return format (plan dict with keys). Explains validation and existence checks. Agent has all needed context to correctly invoke tool.

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, description fully explains operations parameter: dict structure with 'action' key, allowed actions, example. Target parameter described as optional vCenter/ESXi target. Meaningfully supplements schema.

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 tool creates an execution plan for multi-step VM operations. It specifies the resource (plan) and action (create), and distinguishes from siblings like vm_apply_plan which applies the plan.

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?

Explicitly mentions auto-triggering for 2+ steps or VMs, advises showing plan to user before calling vm_apply_plan, and lists allowed actions with example. Provides clear when-to-use and alternative guidance.

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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