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VMware-Monitor

by vmware-skills
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Python
Hybrid

list_all_datastores

Read-onlyIdempotent

List all VMware datastores with capacity, free space, type, and VM count. Use the returned totals to resolve a datastore name, then drill into capacity or investigation tools for detailed analysis.

Instructions

[READ] List datastores with capacity, free space, type, and VM count.

Returns the list envelope with a real total. Raw free/used only — use this to resolve a datastore name, then datastore_capacity for thin-provisioning over-commit risk or datastore_investigation_bundle to drill into one datastore.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax datastores to return (None = all).
targetNovCenter/ESXi target from config (default if omitted).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv1.9.2
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / limit / description
      Added value: +"Max datastores to return (None = all)."
    • addedInput schema / properties / target / description
      Added value: +"vCenter/ESXi target from config (default if omitted)."
    • changedOutput schema / (root)
      Previous value: -{
-  "properties": {
-    "result": {
-      "items": {
-        "additionalProperties": true,
-        "type": "object"
-      },
-      "title": "Result",
-      "type": "array"
-    }
-  },
-  "required": [
-    "result"
-  ],
-  "title": "list_all_datastoresOutput",
-  "type": "object"
-}New value: +null
  2. Changed1 schema field changedv1.5.18
    • addedInput schema / properties / limit
      Added value: +{
+  "anyOf": [
+    {
+      "type": "integer"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Limit"
+}
  3. First observedv0.1.2

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare it read-only, idempotent, non-destructive, and open-world. The description adds useful context beyond annotations by mentioning the 'list envelope with a real total' and 'Raw free/used only', which helps set expectations. It does not contradict any annotation.

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 yet information-dense, with the core purpose in the first line and follow-up guidance in two short sentences. No filler, and the key exclusions and successor tools are front-loaded.

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 simple list operation, the description fully covers what the tool returns (envelope with fields and total), its limitation (raw free/used only), and when to use which alternative. With no output schema, the description adequately explains the return shape and all necessary context for an agent to call 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 coverage is 100%, with both 'limit' and 'target' fully described by the schema. The description does not add parameter-specific detail, which is acceptable given the baseline, but no extra value is provided 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?

States the verb 'List' with a specific resource (datastores) and enumerates the returned fields (capacity, free space, type, VM count). It also names two sibling tools as alternatives, making the tool's purpose and scope unambiguous.

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 states when to use this tool: to resolve a datastore name, and then routes to datastore_capacity or datastore_investigation_bundle for deeper analysis. Also notes that only raw free/used data is provided, implying it is not for thin-provisioning risk assessment.

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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