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service_control

Destructive

Query, start, stop or restart an OS service on the specified registered, authorized online device. device_id selects target, name identifies the Windows Service or macOS launchd job. action is query/status/start/stop/restart; timeout_seconds is clamped to 1–300 (default 30). Mutating actions can disrupt connectivity.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "device_id": "<device_id>",
      "name": "<name>",
      "action": "<action>"
    },
    "name": "service_control"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYes
actionYes
device_idYes
timeout_secondsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true and readOnlyHint=false, so the safety profile is known, but the description adds real value beyond them: the timeout is clamped to 1–300 with a default of 30, and mutating actions can disrupt connectivity. It stops short of noting reversibility or that query/status are the safe read paths in annotation terms.

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?

Three dense sentences, front-loaded with the core action and resource, followed by parameter semantics and then the risk caveat. Nothing is padded and every clause carries information.

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?

With no output schema, the description could say more about what a query/status action returns, which is the only real gap. Everything else an agent needs to invoke it correctly — target, name semantics, action values, timeout bounds, and the disruption caveat — is present.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description carries the full param burden and does so well: device_id selects the target, name identifies the Windows Service or macOS launchd job, action enumerates query/status/start/stop/restart (which the schema does not, since it has no enum), and timeout_seconds is given its range and default. Every parameter is documented meaningfully.

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?

States specific verbs (query, start, stop, restart) and a specific resource (an OS service on a targeted device), immediately distinguishing it from siblings like list_services, kill_process, and run_command. The scope constraints ('specified registered, authorized online device') sharpen it further.

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?

Usage context is implied through the enumerated actions and the prerequisite that the device be registered, authorized, and online, but no alternatives are named and there is no explicit when-not guidance (e.g., use list_services for inventory, kill_process for non-service processes). Adequate but leaves routing to inference.

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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