Skip to main content
Glama

service_status

Check whether a systemd service is active, failed, or running, for system or user units.

Instructions

Check systemd service status (system or user unit)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
userNoCheck user service (--user) instead of system
formatNoOutput formattext
serviceYesService/unit name, e.g. 'docker' or 'podman.socket'
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the basic action ('Check systemd service status') but does not mention that this is a read-only operation, that it may require elevated privileges for system services, or what the output contains beyond 'status'. It also fails to describe the impact of the 'format' parameter on output. This lack of transparency means the agent lacks safety and context information.

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?

The description is a single, concise sentence that front-loads the core action and scope. There is no wasted text, and every word contributes to understanding the tool's purpose. It is appropriately sized for a simple tool with a clear function.

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?

The tool has three parameters and no output schema, so the description should provide context about expected return values or error behavior. The description only states 'Check systemd service status' without explaining what status information is returned or whether output can be formatted as JSON (despite the 'format' parameter). This is a gap, but the tool is relatively simple and the schema covers parameter semantics, so the description is adequate but not comprehensive.

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 provides full descriptions for all three parameters: service (with an example), user (explains --user flag), and format (enum listing text/json). The description adds no additional parameter-level meaning, but since the schema coverage is 100%, the baseline of 3 is appropriate. The description's mention of 'system or user unit' aligns with the 'user' parameter but does not enrich beyond schema documentation.

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?

The description clearly states the tool's function: 'Check systemd service status (system or user unit)'. It specifies a concrete verb ('Check') and resource ('systemd service status'), and the parenthetical clarifies scope (system or user units). This distinguishes it from sibling tools like system_overview or gpu_status, which target different system aspects.

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?

The description implicitly indicates when to use the tool—whenever a systemd service status is needed—but it does not explicitly mention alternatives or exclusion criteria. No guidance is provided about when to prefer another tool (e.g., system_overview for broader system health) or when not to use this tool. The usage context is inferable from the name and description but not directly stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/DTG404/infra-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server