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Clickhouse Query Optimization

Checked
dawiddutoit·vlatest·database

Helps with querying, optimization as part of working with databases and data persistence workflows.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add dawiddutoit/custom-claude --skill clickhouse-query-optimization -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

dawiddutoit

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned dawiddutoit/custom-claude at 17b45a90a6.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
17b45a90a6
Manifest
skills/clickhouse-query-optimization/SKILL.md
Scanned
3 files, 1,160 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill optimizes ClickHouse queries to improve performance and efficiency. It analyzes query structure, indexes, and data types to identify bottlenecks and suggest improvements. The skill aims to reduce query execution time and resource consumption within a ClickHouse database environment.

When to use it

  • You're experiencing slow query times in your ClickHouse database.
  • Your queries are consuming excessive resources (CPU, memory).
  • You need help understanding why a specific ClickHouse query is performing poorly.
  • You want to proactively optimize your ClickHouse environment for better overall performance.

Key capabilities

  • Query analysis and bottleneck identification
  • Index optimization suggestions
  • Data type recommendations
  • General query structure improvements

Example prompts

  • "Optimize this ClickHouse query: SELECT ... FROM ... WHERE ..."
  • "Why is this ClickHouse query so slow?" (followed by the query)
  • "Suggest ways to improve the performance of my ClickHouse database."

Tips & gotchas

This skill requires a valid ClickHouse query as input. The more context provided about the data and schema, the better the optimization suggestions will be.