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

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.
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.
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.

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:

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"
```
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"
```
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.
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"
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.
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"
```
.

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"

Choose Aggregation Structure

Select the

perSeriesAligner

crossSeriesReducer

groupByFields

, and

alignmentPeriod

according to the metric properties and visualization goal:

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 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"
```
.
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.
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
```
  .

Format Valid Request

Present the generated

ListTimeSeries

REST query parameters. For example:

json

{
  "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.

Validate Request via REST API

Always validate the generated request parameters against live Cloud Monitoring telemetry before returning the final output. DO NOT call the

list_timeseries

MCP tool. Perform an HTTP GET request directly to the Cloud Monitoring v3 REST API using

curl -s -H "Authorization: Bearer \$(gcloud auth print-access-token)" -G

with

--data-urlencode

for all query fields (

name

filter

interval.startTime

interval.endTime

aggregation.alignmentPeriod

aggregation.perSeriesAligner

aggregation.crossSeriesReducer

, and

view=HEADERS

). An HTTP 200 OK response confirms that your filter and aggregation settings are valid.

References

Cloud Monitoring ListTimeSeries Basic Aggregations Reference
Cloud Monitoring Monitored Resource Types Reference
Cloud Monitoring Filter Syntax
Cloud Monitoring REST API Reference: projects.timeSeries.list

cloud-monitoring-list-time-series-request

NPX Install

Tags

SKILL.md Content