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vsphere_search_inventory

Read-onlyIdempotent

Search across vSphere object types by name to locate resources and retrieve managed object IDs, even when the object type is unknown.

Instructions

Search the inventory by name across several object types at once.

Useful when you know a name but not what kind of object it is, or when you need the managed object id to pass to another tool.

Args: query: Name to search for (substring, or glob with */?). types: Object types to search. Defaults to all of vm, host, cluster, datastore, network, datacenter, resource_pool and folder. limit: Maximum number of matches to return in total.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes
typesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already indicate a safe read-only, idempotent operation. The description adds useful behavioral detail: substring/glob matching, default object types, and the limit meaning. This goes beyond the annotations, though it does not describe every edge case like null limit behavior, which is acceptable given the existing annotations.

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 concise and well-structured: a clear purpose statement, a usage note, and an Args block. Every sentence adds value, with no fluff or repetition of schema fields.

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 tool's simplicity, the annotations, and the existing output schema, the description provides all necessary context. It explains search behavior, parameter semantics, and when to use it. The output schema covers return values, so no further elaboration is needed.

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?

Schema description coverage is 0%, but the description fully compensates by explaining each parameter: query (substring/glob), types (default list), and limit (maximum total matches). This adds meaningful semantics that the bare input schema lacks.

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 searches the inventory by name across several object types at once. This distinguishes it from sibling tools that list specific object types, and the additional use case of retrieving a managed object ID further clarifies its purpose.

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?

The description explicitly says when to use the tool: when you know a name but not the object type, or when you need a managed object ID. It does not explicitly mention when not to use it or name alternative tools, but the context is clear enough that an agent can infer when a type-specific list/get tool would be more appropriate.

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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