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Python
Hybrid

list_all_datastores

Read-onlyIdempotent

List datastores with capacity, free space, type, and VM count to resolve a datastore name before assessing over-commit risk or investigating one datastore.

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 get_datastore_capacity for thin-provisioning over-commit risk or investigate_datastore 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 readOnly/idempotent/non-destructive, so the safety profile is covered; the description adds meaningful behavior beyond that — it returns raw free/used values only (no derived over-commit analysis) and the list envelope reports a real total rather than a truncated count. It does not mention auth/permission requirements or rate limits, so it stops short of a 5.

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?

Front-loaded with the [READ] marker and the core purpose, then a second sentence devoted entirely to routing. Two sentences, no filler; the minor [READ] redundancy against readOnlyHint costs nothing.

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?

With no output schema, the description carries return-shape responsibility and does so: it enumerates the fields returned and notes the envelope's total semantics. For a simple two-parameter list call with full annotation coverage, nothing an agent needs to invoke it correctly is missing.

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% — limit (None = all) and target are already documented in the schema. The description adds no syntax, default, or format detail beyond that, so the baseline 3 applies.

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?

Specific verb+resource ("List datastores") plus the exact fields returned (capacity, free space, type, VM count). It explicitly names the two sibling tools it is not (get_datastore_capacity, investigate_datastore), so an agent can distinguish it without opening schemas.

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?

Gives an explicit routing rule: use this first to resolve a datastore name, then get_datastore_capacity for thin-provisioning over-commit risk, or investigate_datastore to drill into one datastore. Both the when-to-use and the when-to-use-something-else conditions are stated.

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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