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sacloud

sacloud-mcp

Official
by sacloud

attach_servers

Connect multiple servers to a load balancer in Sakura Cloud to distribute traffic across your infrastructure.

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 lb_id (str): LBのID vip (str): 仮想ipアドレス server_ips (list[str]): 関連づけるサーバのIP

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
lb_idYes
vipYes
server_ipsYes
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 mentions this is a creation operation but doesn't specify permission requirements, whether this is idempotent, rate limits, error conditions, or what happens if the load balancer already exists. For a mutation tool with zero annotation coverage, this is insufficient behavioral context.

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 reasonably structured with purpose statement, Args section, and Returns section. However, the Japanese purpose statement could be more concise, and the overall description could benefit from better organization. It's not overly verbose but could be more efficiently organized.

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 4-parameter mutation tool with no annotations and no output schema, the description provides adequate parameter documentation but lacks behavioral context and output details. The Returns section mentions 'JSON response' but doesn't describe its structure or content. Given the complexity, it's minimally complete but with 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?

With 0% schema description coverage, the description compensates well by providing clear parameter documentation in the Args section. Each of the 4 parameters is named and briefly explained in Japanese, adding meaningful semantics beyond the bare schema. The parameter information is comprehensive and helpful.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

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

The description states the tool 'creates a load balancer' in Japanese, which is a specific verb+resource combination. However, it doesn't distinguish this tool from sibling 'create_loadbalancer' - both appear to create load balancers, creating confusion about their differentiation. The purpose is clear but sibling distinction is missing.

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?

No guidance is provided about when to use this tool versus alternatives like 'create_loadbalancer'. The description doesn't mention prerequisites, constraints, or appropriate contexts for using this specific tool. It simply states what the tool does without usage context.

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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