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mcp-server-qnap-qvs

by arnstarn

get_overview

Retrieve a summary dashboard of all VMs and resource usage: counts, running/stopped states, vCPUs, memory, disk provisioned vs used, and per-VM network details.

Instructions

Get a summary dashboard of all VMs and resource usage.

Returns: VM count, running/stopped breakdown, total vCPUs, memory, disk provisioned vs actual usage, per-VM summary with networking (adapters, MACs, IPs for running VMs).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses the output structure (VM count, running/stopped breakdown, resource usage, networking details) and notes that IPs are for running VMs only, which is a useful behavioral nuance. It doesn't mention performance or permissions, but for a read-only dashboard the transparency is solid.

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?

Two sentences: the first front-loads the main purpose, the second enumerates return contents. Every word earns its place; no filler or redundancy.

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?

For a zero-parameter tool with an output schema, the description is complete. It explains the tool's purpose and explicitly lists the return contents, covering both the dashboard nature and the specific data delivered. No significant gaps.

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?

The tool has zero parameters, and the schema reflects this (100% coverage). Per the rubric, 0 parameters gets a baseline of 4. The description appropriately doesn't need to explain parameter syntax because there are none.

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?

The description clearly states a specific verb and resource: 'Get a summary dashboard of all VMs and resource usage.' This clearly distinguishes it from sibling tools like list_vms (plain list), get_vm (specific VM), and get_vm_states (state info).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use for high-level overviews via 'summary dashboard' and details of returns, but it does not explicitly state when to use this over alternatives or provide exclusion criteria. It lacks explicit 'when-to-use' vs 'when-not-to-use' guidance.

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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