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sjk4425

ncloud-mcp-server

by sjk4425

ncloud_query_monitoring_data

Read-only

Query time-series monitoring data from Cloud Insight to retrieve metric values for a specific product and metric, with support for aggregation and dimension filters.

Instructions

Query time-series monitoring data from Cloud Insight. Returns metric data for a specific product and metric.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cw_keyYesProduct key (cw_key) identifying the service (see Cloud Insight metrics)
metricYesMetric name to query (e.g., "avg_cpu_used_rto", "mem_usert")
timeEndYesEnd time in Unix epoch milliseconds
intervalNoAggregation interval (default: Min5)
prodNameYesProduct name (e.g., "System/Server(VPC)")
timeStartYesStart time in Unix epoch milliseconds
dimensionsNoDimension filters as key-value pairs (e.g., {"instanceNo": "12345"})
aggregationNoAggregation type (default: AVG)
Behavior3/5

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

Annotations already declare readOnlyHint=true, so the description does not need to repeat safety. It adds that it returns metric data for a specific product and metric, but does not disclose potential rate limits, pagination, or error behavior. Adequate but not rich.

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 two sentences, front-loaded with the action, and contains no unnecessary words. Highly concise.

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

Completeness2/5

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

Given the complexity (8 parameters, nested object, no output schema), the description is insufficient. It does not explain the return format, how to interpret results, or how to use the 'dimensions' parameter effectively. This leaves the agent guessing about response handling.

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?

Schema coverage is 100% with detailed parameter descriptions. The tool description adds no further semantic value beyond what is already in the schema, so baseline score of 3 is appropriate.

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 it queries time-series monitoring data and returns metric data for a specific product and metric. However, it does not differentiate from the sibling tool 'ncloud_query_monitoring_data_multiple', which likely queries multiple metrics/products.

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?

No guidance is provided on when to use this tool versus alternatives like 'ncloud_query_monitoring_data_multiple' or 'ncloud_search_events'. The description lacks context for appropriate usage.

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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