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list_vngs

List AWS Ocean virtual node groups with compact summaries or full configurations. Filter by Ocean cluster or account ID.

Instructions

List AWS Ocean Virtual Node Groups (VNGs / launch specs). Returns compact summaries by default (id, name, oceanId). Set verbose=true for full VNG configs (AMI, subnets, resource limits, labels).

Args: ocean_id: Optional Ocean cluster ID to filter by (e.g. o-abc12345) account_id: Optional account ID to query. Defaults to SPOTINST_ACCOUNT_ID env var. verbose: Return full configurations instead of compact summaries (default: false). Use when analyzing VNG settings, troubleshooting, or comparing configs.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_vngs"
  }
}

Input Schema

Name	Required	Description	Default
`ocean_id`	No
`account_id`	No
`verbose`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv0.4.0Apr 30, 2026

addedInput schema / properties / verbose

Added value: +{
+  "default": false,
+  "title": "Verbose",
+  "type": "boolean"
+}

First observedv0.1.0Mar 21, 2026

TDQS

A4.2/5.0

Behavior3/5

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

No annotations provided, so description carries full burden. It discloses behavior for verbose vs. compact output but does not mention read-only nature, authorization needs, or potential performance implications. Adequate but not exceptional.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with main purpose first, then explanation of verbose mode, then parameter list. Could be slightly more concise, but all sentences add value. No fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Describes default output (compact summaries with fields) and verbose output (full configs). Covers parameters and their defaults. Does not mention pagination or limits, but for a list tool with no required params, this is fairly complete.

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 coverage is 0%, but description adds detailed explanations for all three parameters: ocean_id with example, account_id with default behavior, and verbose with use-case guidance. Adds significant value beyond the bare 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?

Clearly states 'List AWS Ocean Virtual Node Groups' with a specific verb and resource. Distinguishes from siblings like get_vng (single) and filter_vngs_by_tag by focusing on listing all VNGs with optional filters.

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?

Provides clear context for when to use verbose mode ('analyzing VNG settings, troubleshooting, or comparing configs'). Also explains optional filters (ocean_id, account_id). Does not explicitly mention alternative tools like get_vng for single VNG or filter_vngs_by_tag for tag-based filtering, but the usage is inferred.

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