Cloudflare GraphQL Analytics for zone traffic, firewall events, Workers metrics, and schema exploration. Use when querying Cloudflare analytics data or exploring the GraphQL API.
日本語の概要は準備中です。原文の説明を表示しています。
Use when working with Azure Monitor — azure Monitor metrics querying, Log Analytics workspace management, alert rule configuration, action groups, and diagnostic settings via Azure CLI.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Manage and analyze Azure Monitor resources using az monitor commands.
ALWAYS discover before acting. Never assume workspace names, alert rule names, metric names, or action group names.
# Discover Log Analytics workspaces
az monitor log-analytics workspace list --output json \
--query "[].{name:name, rg:resourceGroup, sku:sku.name, retentionDays:retentionInDays, dailyCapGB:workspaceCapping.dailyQuotaGb}"
# Discover metric alert rules
az monitor metrics alert list --output json \
--query "[].{name:name, rg:resourceGroup, severity:severity, enabled:enabled, targetResource:scopes[0]}"
ALL independent operations MUST run in parallel using background jobs (&) and wait.
for ws in $(echo "$workspaces" | jq -c '.[]'); do
{
name=$(echo "$ws" | jq -r '.name')
rg=$(echo "$ws" | jq -r '.rg')
az monitor log-analytics workspace show --workspace-name "$name" --resource-group "$rg" --output json
} &
done
wait
# Run a Log Analytics query
run_log_query() {
local workspace="$1" query="$2" timespan="${3:-PT1H}"
az monitor log-analytics query --workspace "$workspace" --analytics-query "$query" --timespan "$timespan" --output json
}
# List available metrics for a resource
list_metrics() {
local resource_id="$1"
az monitor metrics list-definitions --resource "$resource_id" --output json \
--query "[].{name:name.value, displayName:name.localizedValue, unit:unit, aggregations:supportedAggregationTypes}"
}
# Get metric values
get_metrics() {
local resource_id="$1" metrics="$2" interval="${3:-PT1H}" aggregation="${4:-Average}"
az monitor metrics list --resource "$resource_id" --metric $metrics \
--interval "$interval" --aggregation $aggregation --output json
}
# List action groups
list_action_groups() {
local rg="$1"
az monitor action-group list --resource-group "$rg" --output json \
--query "[].{name:name, enabled:enabled, emailReceivers:emailReceivers[].name, smsReceivers:smsReceivers[].name, webhookReceivers:webhookReceivers[].name}"
}
workspaces=$(az monitor log-analytics workspace list --output json --query "[].{name:name, rg:resourceGroup, id:customerId}")
for ws in $(echo "$workspaces" | jq -c '.[]'); do
{
name=$(echo "$ws" | jq -r '.name')
rg=$(echo "$ws" | jq -r '.rg')
ws_id=$(echo "$ws" | jq -r '.id')
az monitor log-analytics workspace show --workspace-name "$name" --resource-group "$rg" --output json \
--query "{name:name, sku:sku.name, retentionDays:retentionInDays, dailyCap:workspaceCapping.dailyQuotaGb, ingestionStatus:workspaceCapping.quotaNextResetTime}"
# Check data volume
run_log_query "$ws_id" "Usage | where TimeGenerated > ago(24h) | summarize DataGB=sum(Quantity)/1024 by DataType | sort by DataGB desc | take 10" "P1D"
} &
done
wait
# Metric alerts
az monitor metrics alert list --output json \
--query "[].{name:name, severity:severity, enabled:enabled, condition:criteria.allOf[0].{metric:metricName,operator:operator,threshold:threshold}, actions:actions[].actionGroupId}"
# Log alerts (scheduled query rules)
az monitor scheduled-query list --output json \
--query "[].{name:name, severity:severity, enabled:enabled, evaluationFrequency:evaluationFrequency, windowSize:windowSize}"
# Activity log alerts
az monitor activity-log alert list --output json \
--query "[].{name:name, enabled:enabled, scopes:scopes, condition:condition}"
# Recent errors across all tables
run_log_query "$WORKSPACE_ID" "union withsource=TableName * | where TimeGenerated > ago(1h) | where Level == 'Error' or severityLevel >= 3 | summarize count() by TableName | sort by count_ desc"
# Heartbeat check for monitored VMs
run_log_query "$WORKSPACE_ID" "Heartbeat | summarize LastHeartbeat=max(TimeGenerated) by Computer | where LastHeartbeat < ago(15m)"
# Ingestion latency
run_log_query "$WORKSPACE_ID" "Heartbeat | where TimeGenerated > ago(1h) | extend IngestionDelay=ingestion_time()-TimeGenerated | summarize avg(IngestionDelay), max(IngestionDelay) by bin(TimeGenerated, 5m)"
# Check diagnostic settings for a resource
az monitor diagnostic-settings list --resource "$RESOURCE_ID" --output json \
--query "[].{name:name, workspace:workspaceId, storageAccount:storageAccountId, eventHub:eventHubAuthorizationRuleId, logs:logs[].{category:category, enabled:enabled, retention:retentionPolicy.days}, metrics:metrics[].{category:category, enabled:enabled}}"
az monitor action-group list --output json \
--query "[].{name:name, rg:resourceGroup, enabled:enabled, email:emailReceivers[].{name:name,address:emailAddress}, sms:smsReceivers[].{name:name,phone:phoneNumber}, webhook:webhookReceivers[].{name:name,uri:serviceUri}, logicApp:logicAppReceivers[].{name:name}, azureFunction:azureFunctionReceivers[].{name:name}}"
Present results as a structured report:
Azure Monitor Report
════════════════════
Resources discovered: [count]
Resource Status Key Metric Issues
──────────────────────────────────────────────
[name] [ok/warn] [value] [findings]
Summary: [total] resources | [ok] healthy | [warn] warnings | [crit] critical
Action Items: [list of prioritized findings]
Target ≤50 lines of output. Use tables for multi-resource comparisons.
--help output.| Shortcut | Counter | Why |
|---|---|---|
| "I'll skip discovery and check known resources" | Always run Phase 1 discovery first | Resource names change, new resources appear — assumed names cause errors |
| "The user only asked for a quick check" | Follow the full discovery → analysis flow | Quick checks miss critical issues; structured analysis catches silent failures |
| "Default configuration is probably fine" | Audit configuration explicitly | Defaults often leave logging, security, and optimization features disabled |
| "Metrics aren't needed for this" | Always check relevant metrics when available | API/CLI responses show current state; metrics reveal trends and intermittent issues |
| "I don't have access to that" | Try the command and report the actual error | Assumed permission failures prevent useful investigation; actual errors are informative |
list-definitions to discover available metrics before querying.PT1H, P1D, P7D), not date ranges.quotaNextResetTime.SELECT instead of project and GROUP BY instead of summarize.まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Cloudflare GraphQL Analytics for zone traffic, firewall events, Workers metrics, and schema exploration. Use when querying Cloudflare analytics data or exploring the GraphQL API.
日本語の概要は準備中です。原文の説明を表示しています。
Use when working with Alloydb — google AlloyDB instance analysis, query insights, columnar engine optimization, maintenance windows, and cluster health.
日本語の概要は準備中です。原文の説明を表示しています。
Use when working with Aqua — aqua Security platform analysis. Covers container runtime protection, image assurance policies, compliance frameworks, vulnerability management, workload protection, and registry scanning. Use when analyzing container security posture, reviewing image compliance, investigating runtime alerts, or auditing security policies.
日本語の概要は準備中です。原文の説明を表示しています。
Use when working with Bigquery — google BigQuery job analysis, slot utilization, cost analysis, dataset management, and query optimization.
日本語の概要は準備中です。原文の説明を表示しています。
Use when working with Cassandra — apache Cassandra keyspace analysis, compaction strategies, repair status, nodetool operations, and cluster health monitoring.
日本語の概要は準備中です。原文の説明を表示しています。
Use when working with Checkov — checkov infrastructure-as-code security scanning. Covers Terraform, CloudFormation, Kubernetes, and Dockerfile scanning, policy management, custom checks, compliance frameworks, and suppression management. Use when scanning IaC for security misconfigurations, evaluating compliance, managing custom policies, or reviewing scan results.
日本語の概要は準備中です。原文の説明を表示しています。