monitor_device_state
Check operational and communication status of measuring devices to quickly identify any that are offline or malfunctioning.
Instructions
측정기 가동/통신 상태 집계를 조회한다.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Check operational and communication status of measuring devices to quickly identify any that are offline or malfunctioning.
측정기 가동/통신 상태 집계를 조회한다.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. '조회한다' implies a read-only query and '집계' indicates aggregated output, which is useful. However, it does not disclose whether the result is real-time or historical, how statuses are represented, or whether any side effects or prerequisites exist.
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, compact sentence that front-loads the subject and action. There is no filler, redundancy, or unnecessary detail.
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?
For a zero-parameter tool, the description is adequate to start a call, but there is no output schema and no annotation context. It would be more complete if it described what the aggregate contains, such as counts of running/stopped/faulty devices or a time scope. The absence of that detail leaves the agent guessing about the return value's meaning.
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 input schema has zero parameters, so the baseline is 4. The description does not need to explain parameters, and it does not introduce any confusion about required inputs.
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 names the operation ('조회한다' / query) and the resource ('측정기 가동/통신 상태 집계' / device operation-communication status aggregate). It is specific enough to convey the tool's core purpose, but it does not explicitly differentiate this from closely related sibling tools like monitor_working_percent or monitor_data_count.
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 given about when to prefer this tool over its many siblings. The description implies it is for querying device status aggregates, but it never states what scenario this fits, what alternatives exist, or what excludes using this tool.
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/arim-science/arimair-mcp'
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