/cloud-monitoring-promql-query

name: cloud-monitoring-promql-query
metadata:
  category: CloudObservabilityAndMonitoring
description: >-
  Generates valid PromQL queries from Cloud Monitoring metric descriptors and
  resource parameters. Use when asked to create, generate, write, or format
  PromQL queries, PromQL strings, or PromQL aggregations for Cloud Monitoring
  metrics and resources. Don't use for raw metric discovery or metric selection.

Cloud Monitoring PromQL Generator

Use this skill to generate a valid PromQL query from any Cloud Monitoring metric type. This guide applies to all Cloud Monitoring metric types by mapping Cloud Monitoring metric and resource descriptors to PromQL structures.

Workflow

Resolve Project ID (CRITICAL & BLOCKING)

Before performing any other actions (such as searching code, reading references, or running validation), you MUST verify whether the Google Cloud Project ID is available:

1. **Check Prompt/Payload**: Look for the Project ID in the user's prompt or input. 2. **Check Environment**: If the Project ID is not present in the prompt, you MUST run `gcloud config get-value project` to attempt to resolve it from the environment. 3. **Ask for Clarification (BLOCKING)**: If the Project ID is not in the prompt AND the `gcloud` command fails, returns an empty string, or is unavailable, you MUST immediately stop. Do NOT generate a PromQL query, do not run the validation script, and do not use placeholders (like `YOUR_PROJECT_ID`). You must refuse to proceed and ask the user to provide the Project ID.

Inspect Metric and Resource Descriptors

1. **Use Provided Descriptors First**: If the user's prompt already includes metric descriptor details (such as `metric.type`, `metricKind`, `valueType`, or `monitoredResourceTypes`) or specific resource filter values, use those values directly instead of calling the Cloud Monitoring API. 2. **Discover Missing Descriptors**: If exact metric descriptors (`metric.type`, `metricKind`, `valueType`) are missing or underspecified, resolve the target metric type's descriptor using one of these paths:

• **Vague Query**: If the prompt is vague (for example, `"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

(for example, `compute.googleapis.com/instance/cpu/utilization`) but need its descriptor, call the `google-cloud-monitoring: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. 3. **Identify Key Fields**: From the retrieved descriptor, identify four 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

required for resource scoping and grouping.

Resolve Resource Filters & Discovery Protocol

To filter data by a specific resource instance, apply these resource rules and discovery protocols:

1. **Monitored Resource Filter**: Always include the `monitored_resource="<type>"` filter in your query to prevent collisions across services that share metric names.

• **Example**: `monitored_resource="gae_app"`

2. **Preserve User Literals (CRITICAL)**: ALWAYS use the literal resource names, namespaces, and IDs provided in the user's prompt. Do **NOT** override or replace these values with active resource names found during Cloud Monitoring discovery unless the user explicitly asked you to find active resources. Telemetry discovery must only be used to identify metric type names and label keys, not to override user input. 3. **Resource Identifier Mapping**:

• **Direct & Specific Keys**: Use the most specific resource identifier

available. **Example**: `version_id`, `cluster_name`.

• **Name-to-ID Resolution**: If the user filters by a resource *name*

(such as `"instance-1"`), but the resource schema uses numeric IDs (like `instance_id`), use PromQL string name labels instead of numeric ID labels. **Example**: `instance_name`, `metadata_system_name`.

• **Composite Identifiers**: For resources with hierarchical identifiers

(such as Cloud SQL databases), format the filter as a single composite key. Do NOT split them into separate `project_id` and sub-resource labels. **Example**: `database_id="{project_id}:{instance_name}"`. 4. **Resource Label Discovery**: The `google-cloud-monitoring:list_metric_descriptors` tool only returns metric-specific labels. If the label schema for a monitored resource is unknown, fetch the resource descriptor directly from the Cloud Monitoring v3 REST API (`projects.monitoredResourceDescriptors.get`):

    TOKEN=$(gcloud auth application-default print-access-token 2>/dev/null || gcloud auth print-access-token)
    curl -s -H "Authorization: Bearer ${TOKEN}" \
    "https://monitoring.googleapis.com/v3/projects/{project_id}/monitoredResourceDescriptors/{monitored_resource_type}"

An HTTP 200 OK response returns the `MonitoredResourceDescriptor` object containing the `labels` array with the exact resource label keys for that resource.

Choose Aggregation Structure & Defaults

The query structure and aggregation functions (such as `rate`, `histogram_quantile`, `sum`, or `avg`) depend on the metric type and how it is visualized.

1. **Consult the Reference**: Consult the [Cloud Monitoring to PromQL Basic Aggregations Reference](ref