vmware-avi

get_ako_amko_status

Read-onlyIdempotent

Check AMKO GSLB status by reading avi-system pods and any GSLBConfig YAML for multi-cluster Kubernetes questions; uses current kubectl context. Not for single-cluster AKO health.

Instructions

[READ] AMKO (AVI Multi-Cluster Kubernetes Operator) GSLB status.

Returns raw kubectl output: the AMKO pods in avi-system, then the GSLBConfig YAML if one exists. 'AMKO not deployed' means kubectl answered and found no AMKO pods; if kubectl cannot read the cluster the call fails with its reason. A GSLBConfig that cannot be read is reported, not skipped. Use this only for multi-cluster GSLB questions — for single-cluster AKO health use get_ako_status instead. Always reads the current kubectl context; see list_ako_clusters.

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": "get_ako_amko_status"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Addedv2.4.0Oct 18, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations cover the safety profile (readOnly, idempotent, non-destructive, openWorld), and the description adds substantial behavioral context beyond them: raw kubectl output shape, the meaning of 'AMKO not deployed', failure behavior when kubectl cannot read the cluster, and that an unreadable GSLBConfig is reported rather than skipped.

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?

Front-loads the [READ] tag and purpose, then layers in output shape and routing guidance; every sentence carries information. Slightly dense and prose-heavy but no filler.

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 an output schema present, return values needn't be re-explained, yet the description still characterizes the output and error semantics. For a zero-param read tool, nothing an agent needs to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Zero parameters, so there is nothing for the description to disambiguate; baseline is 4. The description correctly notes it always reads the current kubectl context, which is the only 'input-like' behavior an agent needs to reason about.

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 a specific verb+resource: retrieving AMKO (AVI Multi-Cluster Kubernetes Operator) GSLB status, and immediately contrasts it with the sibling get_ako_status. An agent can distinguish this from get_ako_status without opening either schema.

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 scopes usage: 'Use this only for multi-cluster GSLB questions — for single-cluster AKO health use get_ako_status instead.' It names the alternative and the condition that selects it, and points to list_ako_clusters for context handling.

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