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Clickhouse System Queries

Community
FrankChen021
clickhouse-system-queries

Query ClickHouse system tables to inspect query logs, monitor cluster health, check replication status, and analyze slow queries. Use when the user mentions "system tables", "query_log", "ClickHouse monitoring", "cluster status", "slow queries", or asks to diagnose ClickHouse operational issues.

Overview

PublisherFrankChen021
Repositorydatastoria
Skill nameclickhouse-system-queries
Stars
327
Forks
18
Bundled files
1
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by FrankChen021 on GitHub. Read the source before you install it.

Installation

Install the Clickhouse System Queries AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/FrankChen021/datastoria/tree/master/resources/skills/clickhouse-system-queries
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/FrankChen021/datastoria.git /tmp/datastoria
mkdir -p .claude/skills
cp -r /tmp/datastoria/resources/skills/clickhouse-system-queries .claude/skills/clickhouse-system-queries
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Clickhouse System Queries in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Clickhouse System Queries on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Clickhouse System Queries is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

ClickHouse System Queries Skill

Use this skill when the user asks for operational inspection on ClickHouse system.* tables.

Current table coverage:

  • system.query_log via references/system-query-log.md

Relationship to sql-expert:

  • sql-expert handles general SQL generation and user/business tables.
  • This skill handles system-table operational patterns and routing to table-specific references.

System Metrics and ProfileEvents

  • Confirm column shape from schema/reference before writing predicates.
  • If the user named an exact metric, pass it in the columns list via explore_schema instead of loading the full table schema.
  • If ProfileEvents is a Map, access entries as ProfileEvents['Name']. If flattened, use ProfileEvent_Name.

Example — map vs flattened access:

sql
-- Map access
SELECT ProfileEvents['DistributedConnectionFailTry'] AS fails
FROM system.query_log WHERE event_date = today();

-- Flattened column access
SELECT ProfileEvent_DistributedConnectionFailTry AS fails
FROM system.query_log WHERE event_date = today();

Workflow

  1. Resolve target — identify system table and intent. Inherit the most recent time window from conversation, or default to last 60 minutes.

  2. Load reference — for system.query_log, call skill_resource to load references/system-query-log.md before writing any SQL. For unsupported tables, fall back to sql-expert.

  3. Execute — choose the right tool:

    • search_query_log for standard ranked searches and filtered lookups
    • execute_sql for visualization, time-bucketed aggregation, trends, or histograms
    sql
    -- search_query_log: standard lookup
    -- finds top 10 slowest queries in the last hour
    
    -- execute_sql: time-bucketed visualization
    SELECT toStartOfFiveMinutes(event_time) AS bucket,
           count() AS queries,
           avg(query_duration_ms) AS avg_ms
    FROM system.query_log
    WHERE event_date = today() AND event_time > now() - INTERVAL 1 HOUR
    GROUP BY bucket ORDER BY bucket

    Default to LIMIT 50 unless the user specifies otherwise.

  4. Summarize with concise findings and next actions.

Guardrails

  • Always apply time bounds for log-like system tables
  • Always use the table-specific reference when available
  • Never generate system.query_log SQL until references/system-query-log.md is loaded in the current turn
  • Never use search_query_log for chart-oriented requests
  • Never omit LIMIT in exploratory queries

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Clickhouse System Queries AI skill do?

Query ClickHouse system tables to inspect query logs, monitor cluster health, check replication status, and analyze slow queries. Use when the user mentions "system tables", "query_log", "ClickHouse monitoring", "cluster status", "slow queries", or asks to diagnose ClickHouse operational issues.

Why use Clickhouse System Queries on TypingMind?

Because you install it once and use it with any model. Clickhouse System Queries is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Clickhouse System Queries in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/FrankChen021/datastoria/tree/master/resources/skills/clickhouse-system-queries. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Clickhouse System Queries?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Clickhouse System Queries?

As many as you like. As long as a model supports skills, you can use Clickhouse System Queries with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Clickhouse System Queries AI skill free?

It is published on GitHub by FrankChen021. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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