
Read-only ClickHouse security audit expert for live or exported systems. Use when assessing ClickHouse security posture, reviewing users, roles, grants, settings profiles, row policies, table functions, external sources, table engines, executable UDFs, audit logs, named collections, password hash hygiene, SQL SECURITY DEFINER, impersonation, TLS/network exposure, Keeper/interserver security, encryption at rest, backups, the HTTP interface surface, cluster security, or version-specific ClickHouse security behavior. Diagnoses from SQL/system tables, supplied configuration files, query logs, access metadata, and ClickHouse/Altinity documentation.
Diagnose and resolve ClickHouse grant and authentication errors, especially after upgrades. Use when queries fail with ACCESS_DENIED/NOT_ENOUGH_PRIVILEGES, AUTHENTICATION_FAILED/WRONG_PASSWORD/REQUIRED_PASSWORD, or ON CLUSTER privilege errors; when system.* or INFORMATION_SCHEMA access is denied; or when grant behavior changes after version upgrades.
Real-time monitoring of ClickHouse metrics, events, and asynchronous metrics. Use for load average, connections, queue monitoring, and resource saturation.
Diagnose ClickHouse Kafka engine health, consumer status, thread pool capacity, and consumption issues. Use for Kafka lag, consumer errors, and thread starvation.
Analyze ClickHouse system log table health including TTL configuration, disk usage, freshness, and cleanup. Use for system log issues and TTL configuration.
Diagnose ClickHouse RAM usage, OOM errors, memory pressure, and allocation patterns. Use for memory-related issues and out-of-memory errors.
Runs a fast ClickHouse server health snapshot and routes to specialist skills. Use as the entry point for general health checks or when the problem area is not yet known.
Track and diagnose ClickHouse ALTER UPDATE, ALTER DELETE, and other mutation operations. Use for stuck mutations and mutation performance issues.
Diagnose ClickHouse issues by analyzing system.part_log (part creation, merges, mutations, downloads, removals, moves). Use for too many parts / micro-batch inserts, merge backlog or slow merges, mutation storms (ALTER DELETE/UPDATE), unusual replication DownloadPart churn, unexpected RemovePart spikes, or ZooKeeper/Keeper znode growth correlated with part activity.
Analyze ClickHouse cache systems including mark cache, uncompressed cache, and query cache. Use for cache hit ratio issues and cache tuning.
Diagnose ClickHouse merge performance, part backlog, and 'too many parts' errors. Use for merge issues and part management problems.
Analyze ClickHouse external dictionaries including configuration, memory usage, reload status, and performance. Use for dictionary issues and load failures.
Diagnose ClickHouse INSERT performance, batch sizing, part creation patterns, and ingestion bottlenecks. Use for slow inserts and data pipeline issues.
Analyze whether ClickHouse indexes (PRIMARY KEY, ORDER BY, skipping indexes, projections) are being used effectively for actual query patterns. Use when investigating index effectiveness, ORDER BY key design, query-to-index alignment, or when queries scan more data than expected.
Diagnose ClickHouse SELECT query performance, analyze query patterns, identify slow queries, and find optimization opportunities. Use for query latency and timeout issues.
Profile a ClickHouse cluster via MCP and emit a per-cluster "analyst" Skill the user can save in claude.ai. Activate when the user asks to "profile this ClickHouse", "generate an analyst skill", "build a schema guide", "map the data in this cluster", or regenerate an existing cluster-analyst Skill after schema changes. Works against any ClickHouse with read-only SELECT/SHOW/DESCRIBE access via an `execute_query` MCP tool (e.g. the Altinity MCP server). Outputs a 5-file markdown bundle plus a README.
Establishes the ClickHouse connection mode, cluster macro, and default log timeframe for diagnostics. Use first, before any other altinity-expert-clickhouse skill, to verify connectivity and set shared analysis rules.
Analyze ClickHouse table structure, partitioning, ORDER BY keys, materialized views, and identify schema design anti-patterns. Use for table design issues and optimization.
Diagnose ClickHouse replication health, Keeper connectivity, replica lag, and queue issues. Use for replication lag and read-only replica problems.
Diagnose ClickHouse disk usage, compression efficiency, part sizes, and storage bottlenecks. Use for disk space issues and slow IO.