clickhouse-io

clickhouse-io is a skill for Claude Code, Codex from ComeOnOliver/skillshub. It costs 26 tokens per session (2,458 once invoked), scanned A, a copy of clickhouse-io, MIT.

A guide to ClickHouse, a database designed for fast analysis of large amounts of data, including table design and query optimization patterns.

In plain words
What is it for?
Use it to design analytics tables, choose MergeTree table types, partition data by date, handle duplicates, and build real-time or distributed reports.
Why use it?
It helps structure analytical data so ClickHouse can scan, compress, and process it efficiently, including data that may arrive more than once.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to design analytics tables, choose MergeTree table types, partition data by date, handle duplicates, and build real-time or distributed reports.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/comeonoliver/skillshub/clickhouse-io
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add ComeOnOliver/skillshub --skill clickhouse-io
Clone the repo
git clone --depth 1 https://github.com/ComeOnOliver/skillshub

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for clickhouse-io

README.md
[![agentmods](https://agentmods.dev/badge/skills/comeonoliver/skillshub/clickhouse-io/github.svg)](https://agentmods.dev/skills/comeonoliver/skillshub/clickhouse-io)
Your own site
<a href="https://agentmods.dev/skills/comeonoliver/skillshub/clickhouse-io"><img src="https://agentmods.dev/badge/skills/comeonoliver/skillshub/clickhouse-io/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for clickhouse-io

Your own site · 80×15
<a href="https://agentmods.dev/skills/comeonoliver/skillshub/clickhouse-io"><img src="https://agentmods.dev/badge/skills/comeonoliver/skillshub/clickhouse-io.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,458 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 80% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00026 $0.02458
Opus 5 $0.00013 $0.01229
Sonnet 5 $0.00005 $0.00492
Haiku 4.5 $0.00003 $0.00246

Measured 10d ago against content hash 500ff44e9e60, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

clickhouse-io scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

80% identical to clickhouse-io — 132 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/Bamose/everything-codex-cli/clickhouse-io/SKILL.md · 431 lines

How it starts

The opening of the file, as written. The whole thing — 431 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ClickHouse Analytics Patterns

ClickHouse-specific patterns for high-performance analytics and data engineering.

Overview

ClickHouse is a column-oriented database management system (DBMS) for online analytical processing (OLAP). It's optimized for fast analytical queries on large datasets.

Key Features:

  • Column-oriented storage
  • Data compression
  • Parallel query execution
  • Distributed queries
  • Real-time analytics

Table Design Patterns

MergeTree Engine (Most Common)

CREATE TABLE markets_analytics (
    date Date,
    market_id String,
    market_name String,
    volume UInt64,
    trades UInt32,
    unique_traders UInt32,
    avg_trade_size Float64,
    created_at DateTime
) ENGINE = MergeTree()
PARTITION BY toYYYYMM(date)
ORDER BY (date, market_id)
SETTINGS index_granularity = 8192;

ReplacingMergeTree (Deduplication)

-- For data that may have duplicates (e.g., from multiple sources)
CREATE TABLE user_events (
    event_id String,
    user_id String,
    event_type String,
    timestamp DateTime,
    properties String
) ENGINE = ReplacingMergeTree()
PARTITION BY toYYYYMM(timestamp)
ORDER BY (user_id, event_id, timestamp)
PRIMARY KEY (user_id, event_id);

AggregatingMergeTree (Pre-aggregation)

-- For maintaining aggregated metrics
CREATE TABLE market_stats_hourly (
    hour DateTime,
    market_id String,
    total_volume AggregateFunction(sum, UInt64),
    total_trades AggregateFunction(count, UInt32),
    unique_users AggregateFunction(uniq, String)
) ENGINE = AggregatingMergeTree()
PARTITION BY toYYYYMM(hour)
ORDER BY (hour, market_id);

-- Query aggregated data
SELECT
    hour,
    market_id,
    sumMerge(total_volume) AS volume,
    countMerge(total_trades) AS trades,
    uniqMerge(unique_users) AS users
FROM market_stats_hourly
WHERE hour >= toStartOfHour(now() - INTERVAL 24 HOUR)
GROUP BY hour, market_id
ORDER BY hour DESC;

Query Optimization Patterns

Efficient Filtering

-- ✅ GOOD: Use indexed columns first
SELECT *
FROM markets_analytics
WHERE date >= '2025-01-01'
  AND market_id = 'market-123'
  AND volume > 1000
ORDER BY date DESC
LIMIT 100;

-- ❌ BAD: Filter on non-indexed columns first
SELECT *
FROM markets_analytics
WHERE volume > 1000
  AND market_name LIKE '%election%'
  AND date >= '2025-01-01';

Read the full file on GitHub · 431 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 431 lines · 26 tokens per session scan A 500ff44e9e60

Subscribe to this mod's changes

clickhouse-io is a skill published in the GitHub repository ComeOnOliver/skillshub (63 stars, last pushed 2mo ago), licensed MIT. It adds 26 tokens to every session and 2,458 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 80% identical to clickhouse-io, differing in 132 lines, and is treated as a copy.

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