Skip to main content
Glama
vmware-skills

vmware-aria

by vmware-skills
OverviewSchemaSourceRelated ServersScoreDiscussionsAdmin
Python
Remote

get_top_consumers

Read-onlyIdempotent

Identify top resource consumers by a specified metric to pinpoint capacity hotspots, then drill into their metric history.

Instructions

[READ] Query resources with highest consumption of a given metric. Then call get_resource_metrics on a returned id for its history.

Returns a paginated envelope: items, returned, limit, total (null when the API reports no size), truncated, hint. Check truncated before calling this the complete set.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
top_nNoNumber of top consumers to return (max 50). Default 10.
targetNoAria target name from config; default when omitted.
metric_keyNoMetric to rank by, e.g. cpu|usage_average, mem|usage_average, disk|usage_average.cpu|usage_average
resource_kindNoResource kind to scope the query. Default VirtualMachine.VirtualMachine

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changedv1.10.0
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / metric_key / description
      Added value: +"Metric to rank by, e.g. cpu|usage_average, mem|usage_average, disk|usage_average."
    • addedInput schema / properties / resource_kind / description
      Added value: +"Resource kind to scope the query. Default VirtualMachine."
    • addedInput schema / properties / target / description
      Added value: +"Aria target name from config; default when omitted."
    • addedInput schema / properties / top_n / description
      Added value: +"Number of top consumers to return (max 50). Default 10."
  2. Changed1 schema field changedv1.8.9
    • changedOutput schema / (root)
      Previous value: -{
-  "properties": {
-    "result": {
-      "items": {
-        "additionalProperties": true,
-        "type": "object"
-      },
-      "title": "Result",
-      "type": "array"
-    }
-  },
-  "required": [
-    "result"
-  ],
-  "title": "get_top_consumersOutput",
-  "type": "object"
-}New value: +null
  3. Addedv1.5.29
  4. Removedv1.5.28
  5. First observedv1.3.2

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the readOnly/openWorld/idempotent annotations, the description discloses the paginated envelope fields, the null total behavior, and the critical truncated caveat. This tells the agent that a returned result may be incomplete and to check truncated before trusting the full set.

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 compact, front-loaded with the primary purpose, and uses a second sentence for essential result handling. Every sentence contributes useful information without padding.

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?

There is no output schema, so the description compensates by specifying the return envelope and truncation behavior. With read-only annotations, four fully documented optional parameters, and a clear follow-up via get_resource_metrics, an agent has enough context to call and interpret this tool 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 schema already documents all four parameters. The description adds only general mapping like 'given metric' to metric_key and resources to resource_kind, but no additional parameter semantics beyond the 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 names a specific operation: query resources with the highest consumption of a given metric. It also distinguishes itself from get_resource_metrics by positioning that sibling as a follow-up for history. The [READ] prefix is consistent and makes intent obvious.

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 gives clear context for when to use this tool: when you need top consumers of a metric. It also points to get_resource_metrics for the next step, but it does not explicitly state when NOT to use this tool or mention alternatives like list_resources.

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

Install Server

Other Tools