cloud-monitoring-list-time-series-request

Cloud Monitoring ListTimeSeries Request Generator

Use this skill to translate any Cloud Monitoring metric descriptor into valid,

production-ready ListTimeSeries REST API query parameters (name, filter,

interval.startTime, interval.endTime, aggregation.*, view).

CRITICAL RULES

• Mandatory Project ID Clarification: You MUST ensure the GCP Project ID

is present in the user prompt, input payload, or environment context (such

as via gcloud config get-value project). If the Project ID is missing and

cannot be resolved, you MUST ask the user to clarify it before generating or

executing ListTimeSeries requests. Do NOT use placeholders for project

names.

Workflow

Inspect Metric Metadata

1. Use Provided Metric Metadata First: If the user's prompt already

includes metric metadata such as metric.type, metricKind, valueType,

resource types, or label keys, use those values directly instead of calling

API tools.

1. Discover Missing Metadata: If exact metric descriptors including

metric.type, metricKind, and valueType are missing or underspecified,

resolve the target metric's descriptor using one of these paths:

• Vague Query: If the prompt is vague, such as asking for VM CPU

usage, use the cloud-monitoring-metric-selection skill first to

identify the specific metric type.

• Known Metric Type: If you already have the specific metric type name

such as compute.googleapis.com/instance/cpu/utilization, but need its

descriptor, call the list_metric_descriptors MCP tool. If the tool is

missing, refer to the cloud-monitoring-metric-selection skill to

configure the Cloud Monitoring MCP server.

• Fallback: If the MCP tool cannot be configured, fall back to making

a direct Cloud Monitoring API call.

1. Identify Key Fields: From the retrieved descriptor, identify key schema

attributes:

• type: The Cloud Monitoring metric type string.
• metricKind: GAUGE, DELTA, or CUMULATIVE.
• valueType: INT64, DOUBLE, DISTRIBUTION, or BOOL.
• monitoredResourceTypes: Compatible resource.type strings, for

example ["cloudsql_database", "cloudsql_instance"]. If multiple

resource types are listed, select the specific resource.type that

matches the target granularity of the user's request.

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Construct Monitoring Filter

The filter parameter is a mandatory string in Cloud Monitoring syntax that

restricts the query to a single metric.type and optional resource and metric

labels:

1. Single Metric Type Restriction: Every filter MUST specify exactly one

metric.type clause using an equality operator. For example:

• metric.type = "compute.googleapis.com/instance/cpu/utilization"

1. Monitored Resource Type Filter: MUST include the resource.type filter

when the target resource granularity is known, preventing collisions across

services that share metric types or sub-resources. For example:

• `metric.type = "cloudsql.googleapis.com/database/cpu/utilization" AND

resource.type = "cloudsql_database"`

1. Preserve User Literals and IDs: You MUST use literal resource names,

IDs, zones, and project parameters provided by the user without alteration.

Do NOT override or replace user-specified identifiers with active resources

found during metric metadata discovery unless explicitly requested.

1. Label Type Prefixing:

• Prefix resource-level dimensions, such as instance ID, zone, project,

database ID, or subscription ID, with the resource.labels. prefix. For

example:

• resource.labels.instance_id = "123456789"
• resource.labels.database_id = "my-project:my-instance"
• Prefix metric-level dimensions, such as state, command, response code,

or instance name metadata when stored on the metric, with the

metric.labels. prefix. For example:

• metric.labels.state != "free"
• metric.labels.instance_name = "instance-1"

1. Resource Name versus ID Resolution:

• If the user specifies a human-readable GCE VM instance name such as

"instance-1", but resource.labels.instance_id expects a numeric ID,

you MUST filter using either `metric.labels.instance_name =

"instance-1" or metadata.system_labels.name = "instance-1"`.

• Do NOT use resource.metadata.name or resource.metadata.*. This

prefix is invalid in Cloud Monitoring filter syntax.

• Do NOT assign a string instance name directly to

resource.labels.instance_id unless the resource type explicitly uses

string IDs.

1. Database Identifier Labels: Database labels such as database_id for

Cloud SQL and Spanner, or dataset_id for BigQuery, use composite keys

formatted as <project_id>:<instance_name>. For example:

resource.labels.database_id = "my-project:foo".

1. Ops Agent Metrics State Label Filtering: For

agent.googleapis.com/memory/percent_used and

agent.googleapis.com/disk/percent_used metrics, you MUST use

metric.labels.state != "free". Do NOT filter by `metric.labels.state =

"used"`.

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Choose Aggregation Structure

Select the perSeriesAligner, crossSeriesReducer, groupByFields, and

alignmentPeriod according to the metric properties and visualization goal:

1. Consult the Aggregations Reference: You MUST include both

perSeriesAligner and crossSeriesReducer in the aggregation query

parameters of every request. Read and follow the

[Cloud Monitoring ListTimeSeries Basic Aggregations Reference](references/basic_aggregations.md)

to select the exact perSeriesAligner and crossSeriesReducer combinations

for your metric's Metric Kind and Value Type pairing, and to apply mandatory

SRE rules for utilization metrics, counters, distributions, and state-based

gauges such as memory filtered by state != "free".

1. Grouping Fields and Resource Granularity: When crossSeriesReducer is

specified as anything other than REDUCE_NONE, list the exact labels to

preserve. When querying multi-instance resources like VMs, databases, or

subscriptions, include the primary resource identifier in groupByFields.

For example, use resource.labels.instance_id for VMs or

resource.labels.database_id for databases. This prevents collapsing

separate resource streams into a single global aggregate.

1. Alignment Period Determination: Calculate the query lookback duration

from endTime minus startTime, ensuring startTime precedes endTime.

If endTime <= startTime, flag an error before computing duration. Set

alignmentPeriod according to Cloud Console default fine granularity

standards:

• Duration <= 110 minutes: Set alignmentPeriod = "60s".
• Duration <= 23 hours: Set alignmentPeriod = "300s".
• Duration <= 6 days: Set alignmentPeriod = "3600s".
• Duration <= 23 days: Set alignmentPeriod = "10800s".
• Duration <= 80 days: Set alignmentPeriod = "21600s".
• Duration <= 180 days: Set alignmentPeriod = "43200s".
• Duration <= 350 days: Set alignmentPeriod = "86400s".
• Duration <= 500 days: Set alignmentPeriod = "172800s".
• Omission Rule: alignmentPeriod is omitted only when

perSeriesAligner is set to ALIGN_NONE.

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Format Valid Request

Present the generated ListTimeSeries REST query parameters. For example:

{
  "name": "projects/<project_id>",
  "filter": "metric.type = \"<metric_type>\" AND resource.type = \"<resource_type>\"",
  "interval": {
    "startTime": "<iso_8601_start>",
    "endTime": "<iso_8601_end>"
  },
  "aggregation": {
    "alignmentPeriod": "60s",
    "perSeriesAligner": "ALIGN_RATE",
    "crossSeriesReducer": "REDUCE_SUM",
    "groupByFields": [
      "resource.labels.zone"
    ]
  },
  "view": "FULL"
}

• Aggregation Requirements: Populate the aggregation parameters with the

perSeriesAligner, crossSeriesReducer, alignmentPeriod, and optional

groupByFields values determined during aggregation selection.

• Interval Requirements: startTime and endTime MUST be valid RFC 3339

and ISO 8601 timestamps such as "YYYY-MM-DDTHH:MM:SSZ". If not explicitly

provided by the user, dynamically compute a one-hour lookback interval

ending at the current time, where endTime is the present moment and

startTime is one hour prior. Do NOT hardcode static dates from examples.

• Alignment Period Requirement: Determine alignmentPeriod from the

lookback duration of endTime minus startTime using the mapping above.

For the default one-hour lookback interval, alignmentPeriod is "60s".

• View Requirement: MUST default to "FULL" when time series data points

are needed, or "HEADERS" when inspecting metadata and series identities

only.

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Validate Request via list_timeseries MCP Tool

You MUST validate the generated request parameters against live Cloud Monitoring

telemetry before returning the final output. Call the list_timeseries MCP tool

passing all generated query parameters (name, filter, interval,

aggregation). When validating you MUST set view="HEADERS" to minimize

latency and payload size while verifying request structure. A response without

API errors confirms that your filter and aggregation settings are valid.

If the list_timeseries tool is unavailable, fall back to a direct API call.

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References

• [Cloud Monitoring ListTimeSeries Basic Aggregations Reference](references/basic_aggregations.md)
• Cloud Monitoring Monitored Resource Types Reference
• Cloud Monitoring Filter Syntax
• Cloud Monitoring REST API Reference: projects.timeSeries.list