get_server_plan
Retrieve available server plans from Sakura Cloud API to compare specifications and pricing for infrastructure deployment.
Instructions
さくらのクラウドAPIからサーバプラン一覧を取得します
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| zone | Yes |
Retrieve available server plans from Sakura Cloud API to compare specifications and pricing for infrastructure deployment.
さくらのクラウドAPIからサーバプラン一覧を取得します
| Name | Required | Description | Default |
|---|---|---|---|
| zone | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states this is a retrieval operation but doesn't mention whether it's read-only, safe, requires authentication, has rate limits, returns paginated results, or what format the output takes. For a tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Japanese that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded with the core action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no annotations, no output schema, and 0% schema description coverage for its one required parameter, the description is incomplete. It doesn't explain what a server plan is, what the output looks like, or provide any behavioral context, making it inadequate for an agent to use confidently without external knowledge.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description doesn't mention any parameters, and schema description coverage is 0% (the 'zone' parameter has no description in the schema). However, with only one parameter, the baseline is 4, but it's reduced to 3 because the description provides no context about what 'zone' means or why it's required, leaving the agent to guess based on the tool name and sibling tools.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('取得します' - retrieve/get) and resource ('サーバプラン一覧' - server plan list) from a specific API source ('さくらのクラウドAPI' - Sakura Cloud API). It's specific about what it retrieves, though it doesn't explicitly differentiate from sibling tools like get_disk_plan or get_server_list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, context, or comparisons with sibling tools like get_server_list or get_disk_plan, leaving the agent to infer usage based on tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/sacloud/sacloud-mcp'
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