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 Singlestore — singleStore (MemSQL) workspace management, pipeline status, query tuning, memory analysis, and cluster health.
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。
Analyze and optimize SingleStore clusters with safe, read-only operations.
You MUST follow this two-phase pattern. Skipping Phase 1 causes hallucinated database/table names.
#!/bin/bash
# 1. Cluster info
singlestore -h "$SS_HOST" -P "$SS_PORT" -u "$SS_USER" -p"$SS_PASSWORD" -e "SHOW CLUSTER STATUS;"
# 2. List databases
singlestore -h "$SS_HOST" -P "$SS_PORT" -u "$SS_USER" -p"$SS_PASSWORD" -e "SHOW DATABASES;"
# 3. List tables
singlestore -h "$SS_HOST" -P "$SS_PORT" -u "$SS_USER" -p"$SS_PASSWORD" -e "SHOW TABLES FROM my_database;"
# 4. Describe table (never assume column names)
singlestore -h "$SS_HOST" -P "$SS_PORT" -u "$SS_USER" -p"$SS_PASSWORD" -e "DESCRIBE my_database.my_table;"
# 5. Table types (rowstore vs columnstore)
singlestore -h "$SS_HOST" -P "$SS_PORT" -u "$SS_USER" -p"$SS_PASSWORD" -e "SELECT TABLE_NAME, TABLE_TYPE, ENGINE FROM information_schema.tables WHERE TABLE_SCHEMA = 'my_database';"
Phase 1 outputs:
Only reference databases, tables, and columns confirmed in Phase 1.
#!/bin/bash
# Core SingleStore query runner — always use this
ss_query() {
local query="$1"
mysql -h "${SS_HOST:-localhost}" -P "${SS_PORT:-3306}" \
-u "${SS_USER:-root}" -p"${SS_PASSWORD}" \
-N -B -e "$query"
}
SHOW PIPELINESLIMIT to user table queriesEXPLAIN before running expensive queries#!/bin/bash
echo "=== Cluster Status ==="
ss_query "SHOW CLUSTER STATUS;"
echo ""
echo "=== Aggregators ==="
ss_query "SHOW AGGREGATORS;"
echo ""
echo "=== Leaves ==="
ss_query "SHOW LEAVES;"
echo ""
echo "=== Memory Usage ==="
ss_query "SELECT @@maximum_memory, @@maximum_table_memory;"
ss_query "SELECT DATABASE_NAME, SUM(MEMORY_USE)/1024/1024 as memory_mb FROM information_schema.TABLE_STATISTICS GROUP BY DATABASE_NAME ORDER BY memory_mb DESC;"
#!/bin/bash
DB="${1:-my_database}"
echo "=== Pipelines ==="
ss_query "USE $DB; SHOW PIPELINES;"
echo ""
echo "=== Pipeline Status ==="
ss_query "USE $DB; SELECT * FROM information_schema.PIPELINES_CURSORS;" 2>/dev/null
echo ""
echo "=== Pipeline Errors ==="
ss_query "USE $DB; SELECT PIPELINE_NAME, BATCH_ID, PARTITION, BATCH_STATE FROM information_schema.PIPELINES_BATCHES_SUMMARY WHERE BATCH_STATE = 'Error' LIMIT 10;" 2>/dev/null
#!/bin/bash
echo "=== Resource Pool Status ==="
ss_query "SHOW RESOURCE POOLS;"
echo ""
echo "=== Plancache ==="
ss_query "SELECT DATABASE_NAME, SUBSTR(QUERY_TEXT, 1, 80) as query, EXECUTION_COUNT, AVG_RUNTIME, AVG_ROWS_RETURNED FROM information_schema.MV_PLANCACHE ORDER BY AVG_RUNTIME DESC LIMIT 15;"
echo ""
echo "=== Running Queries ==="
ss_query "SHOW PROCESSLIST;" | head -20
#!/bin/bash
echo "=== Database Sizes ==="
ss_query "SELECT TABLE_SCHEMA, SUM(DATA_LENGTH + INDEX_LENGTH)/1024/1024 as size_mb, COUNT(*) as tables FROM information_schema.tables GROUP BY TABLE_SCHEMA ORDER BY size_mb DESC;"
echo ""
echo "=== Columnstore Segments ==="
ss_query "SELECT DATABASE_NAME, TABLE_NAME, SUM(ROWS_COUNT) as total_rows, COUNT(*) as segments FROM information_schema.COLUMNAR_SEGMENTS GROUP BY DATABASE_NAME, TABLE_NAME ORDER BY total_rows DESC LIMIT 15;" 2>/dev/null
echo ""
echo "=== Memory by Table ==="
ss_query "SELECT DATABASE_NAME, TABLE_NAME, MEMORY_USE/1024/1024 as memory_mb, ROWS as row_count FROM information_schema.TABLE_STATISTICS ORDER BY MEMORY_USE DESC LIMIT 15;"
Present results as a structured report:
Analyzing Singlestore 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.
| 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 |
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。