A structured review of ClickHouse schema, query and insertion choices with links to focused rules.
Editorial review checked 2026-10-29 against this instruction snapshot. Supporting scripts and runtime behavior remain outside this editorial review.
The source organizes a broad rule library around storage layout, data types, query execution and ingestion. It also routes connection and query-safety setup separately. Its useful output is a traceable list of checked rules and concrete findings, rather than an unexplained claim that a schema is optimized.
Reviewing an existing ClickHouse design or preparing a change to sort keys, partitions, joins or batching behavior.
This is specific to ClickHouse; generic relational indexing intuition can mislead. Rule coverage is not exhaustive, and repository instructions can lag product releases. Administrative commands and heavy diagnostic queries require their own permission and resource review.
Unknown; inspect source requirements and supporting scripts.
Inspect the pinned source snapshot and its supporting files first. The command selects this skill through the open-source skills CLI. Node.js and agent-specific setup may be required. Installation can download code; this catalog never runs it.
npx skills add https://github.com/ClickHouse/agent-skills/tree/69a8354b05b5942e5cea77b6c87be7788303fc18/skills/clickhouse-best-practices --skill clickhouse-best-practicesReview pinned skill folder ↗ · CLI documentation ↗
After source review, use npx skills check and npx skills update to inspect and apply upstream updates. Re-check changed instructions before running them.
Static review only. This is not a security audit or a guarantee of safety.
SKILL.md text only; scripts, dependencies and runtime behavior not audited.
Allowed tools declaration: Unknown. Runtime permissions and network behavior: Unknown.
86/100 · Metadata coverage 100% · Model 1.0
Scores summarize observable discovery signals. Popularity and repository activity apply to the whole repository. Unknown runtime safety earns no certification.
Identify the table engine and representative query predicates, then read only the matching schema and query references. Prioritize findings by their measured effect on the actual workload.
Compare query plans and resource usage before and after a proposed change on a bounded fixture. Verify insertion behavior and retention needs as well as read latency; avoid destructive experiments on the only copy of a table.
Related by category; compare scope and dependencies before choosing an alternative.
Explore 360 feedback system as a data & databases workflow from sickn33/agentic-awesome-skills. Compare its source, maintenance and review signals before choosing it for your agent.
Explore access matrix as a data & databases workflow from sickn33/agentic-awesome-skills. Compare its source, maintenance and review signals before choosing it for your agent.
Explore adhx as a data & databases workflow from sickn33/agentic-awesome-skills. Compare its source, maintenance and review signals before choosing it for your agent.
A Python DataFrame workflow for exploring files and joining tabular sources through the embedded ClickHouse engine.
Embedded analytical SQL for Python tasks that need ClickHouse functions without operating a separate database server.
A workload-first decision aid for ClickHouse ingestion, enrichment, time-series storage and changing data.