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sacloud

sacloud-mcp

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by sacloud

create_loadbalancer

Create a load balancer in Sakura Cloud to distribute network traffic across servers, specifying zone, IP address, switch connection, and network configuration parameters.

Instructions

さくらのクラウドAPIでロードバランサを作成します Args: zone (str): 作成対象のゾーン name (str): ロードバランサ名(1-64文字) description (str, optional): ルータの説明(最大512文字) lb_ip (str) ロードバランサに付与されるip address switch_id (str): 紐付けるスイッチのID vrid (str): (1から255) network_mask (str): プレフィックス長(8~29) default_router(str, optional) ゲートウェイ

Returns: dict: 作成されたロードバランサのJSONレスポンス

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
zoneYes
nameYes
descriptionYes
lb_ipYes
switch_idYes
vridYes
netwrok_maskYes
default_routerYes
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states this creates a load balancer (implying a write/mutation operation) but doesn't mention required permissions, rate limits, costs, or what happens on failure. The Returns section mentions a JSON response but doesn't describe its structure or what success/failure looks like.

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

Conciseness3/5

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

The description is appropriately sized but not optimally structured. The main purpose statement is clear, but the parameter documentation uses inconsistent formatting (some have type hints, some don't) and contains a typo ('netwrok_mask' vs schema's 'network_mask'). The Returns section is minimal but adequate. Overall functional but could be cleaner.

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

Completeness3/5

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

For a creation tool with 8 parameters, no annotations, and no output schema, the description provides adequate parameter semantics but lacks behavioral context. It covers what parameters mean but not how the tool behaves operationally. Given the complexity of creating infrastructure resources, more guidance on permissions, costs, or error handling would be beneficial.

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?

With 0% schema description coverage, the description compensates well by providing Japanese explanations for all 8 parameters, including constraints like name length (1-64 characters), description max length (512 characters), vrid range (1-255), and network mask range (8-29). It also indicates which parameters are optional (description, default_router). This 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.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('作成します' - creates) and resource ('ロードバランサ' - load balancer) in the Sakura Cloud API context. It distinguishes from siblings like create_router or create_switch by specifying load balancer creation. However, it doesn't explicitly differentiate from other creation tools beyond naming the resource.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like create_router or create_switch. There's no mention of prerequisites, dependencies, or typical use cases. The agent must infer usage from the tool name and parameter list alone.

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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