vmware-avi

get_ako_sync_status

Read-onlyIdempotent

Compare Kubernetes Ingress counts with AVI Virtual Service counts to check AKO sync status, returning both totals and a match/mismatch verdict before deeper diffing.

Instructions

[READ] Compare the number of K8s Ingresses with the number of AVI Virtual Services.

Returns both counts and a match/mismatch verdict. Use this first as a cheap check, then diff_ako_sync for which objects differ. A count comparison only — in AKO shard mode many Ingresses share one VS, so a mismatch does not by itself mean trouble.

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_sync_status"
  }
}

Input Schema

Name	Required	Description	Default
`context`	No	K8s context name (optional).

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Addedv2.4.0Oct 18, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint/idempotentHint/destructiveHint=false, so safety is covered. The description adds real behavioral context beyond that: it is a cheap, count-only check, and a mismatch is a false positive in AKO shard mode where many Ingresses share one VS. It does not discuss error behavior or rate limits, so it falls just short of the top.

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?

Four short sentences, front-loaded with the operation and its return, then the workflow ordering, then the caveat. Every sentence carries distinct information with no restatement of the name or schema.

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?

Output schema exists, so return values need no explanation here, and the description supplies the two things an agent cannot infer: that this is a cheap pre-check before diff_ako_sync, and that mismatches are expected in shard mode. Nothing needed to call or interpret the tool 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?

There is a single optional 'context' parameter with 100% schema description coverage ('K8s context name (optional)'), so the schema fully documents it. The description adds nothing about the parameter, which is the expected baseline when the schema does the work.

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 precise verb and two concrete resources ('Compare the number of K8s Ingresses with the number of AVI Virtual Services') and names the output ('both counts and a match/mismatch verdict'). It is clearly distinguishable from diff_ako_sync, which it explicitly names as the finer-grained sibling.

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?

'Use this first as a cheap check, then diff_ako_sync for which objects differ' gives explicit ordering and names the alternative tool for the follow-up step. The shard-mode caveat adds a when-to-distrust condition, covering both when to use and when a result is not actionable.

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