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OrbStack MCP Server

by heresun

orbstack_machine_info

Read-onlyIdempotent

Retrieve detailed information about a specific Linux machine, including distribution, architecture, status, and IP address.

Instructions

获取指定 Linux 机器的详细信息。

包括发行版、架构、状态、IP 地址等。

Args: params: 包含机器名称

Returns: str: 机器详细信息

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The `orbstack_machine_info` tool definition and handler implementation. It uses `_run_orb` to fetch details for a specified machine.
    @mcp.tool(
        name="orbstack_machine_info",
        annotations={
            "title": "查看 Linux 机器详情",
            "readOnlyHint": True,
            "destructiveHint": False,
            "idempotentHint": True,
            "openWorldHint": False,
        },
    )
    async def orbstack_machine_info(params: MachineNameInput) -> str:
        """获取指定 Linux 机器的详细信息。
    
        包括发行版、架构、状态、IP 地址等。
    
        Args:
            params: 包含机器名称
    
        Returns:
            str: 机器详细信息
        """
        code, stdout, stderr = await _run_orb(["info", params.name])
        if code != 0:
            return _format_error(stderr)
        return f"机器 '{params.name}' 详情:\n{stdout}"
  • The `MachineNameInput` schema used by `orbstack_machine_info` and other tools, which validates the machine name input.
    class MachineNameInput(BaseModel):
        """需要机器名称的输入参数"""
        model_config = ConfigDict(str_strip_whitespace=True, extra="forbid")
    
        name: str = Field(
            ...,
            description="Linux 机器的名称",
            min_length=1,
Behavior3/5

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

Annotations provide readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=false, covering safety and idempotency. The description adds context by specifying it returns details like distribution, architecture, status, and IP addresses, which helps the agent understand the return format. However, it doesn't disclose behavioral traits beyond this, such as rate limits or authentication needs, leaving some gaps despite the annotations.

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

Conciseness4/5

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

The description is appropriately sized and front-loaded, starting with the main purpose followed by examples and parameter/return info. It uses three clear sections (purpose, Args, Returns) with minimal waste. However, the inclusion of 'Args:' and 'Returns:' labels adds slight redundancy, as this info is partly covered elsewhere, preventing a perfect score.

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

Completeness4/5

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

Given the tool's low complexity (1 parameter), rich annotations (readOnly, idempotent, etc.), and the presence of an output schema (implied by 'Returns: str'), the description is mostly complete. It explains what the tool does and what information it returns, though it could benefit from more usage guidance relative to siblings. The annotations and schema handle safety and structure well, so the description adds sufficient value.

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?

The input schema has 0% description coverage, but the description compensates by stating '包含机器名称' (contains machine name) and listing the parameter in the Args section. This adds meaning beyond the schema, which only defines the parameter structure without explaining its purpose. However, it doesn't provide detailed semantics like format constraints or examples, so it's adequate but not comprehensive.

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 tool's purpose: '获取指定 Linux 机器的详细信息' (Get detailed information about a specified Linux machine). It specifies the verb ('获取' - get) and resource ('Linux 机器' - Linux machine), and lists examples of information included. However, it doesn't explicitly differentiate from sibling tools like 'orbstack_machine_list' or 'orbstack_status', which is why it doesn't earn a 5.

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. It doesn't mention sibling tools like 'orbstack_machine_list' (which lists machines) or 'orbstack_status' (which might provide status information), nor does it specify prerequisites or exclusions. The only implied usage is when you need details for a specific machine, but this is minimal 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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