clickhouse-io

clickhouse-io is a skill for Claude Code, Codex from JSK9999/ai-nexus. It costs 26 tokens per session (2,458 once invoked), scanned A, a copy of clickhouse-io, Apache-2.0.

Guidance for ClickHouse, a column-oriented database built for analyzing large amounts of data. It covers table design, queries, and data-engineering patterns.

In plain words
What is it for?
Designing MergeTree tables, handling duplicates with ReplacingMergeTree, partitioning data, optimizing queries, and building real-time analytics workflows.
Why use it?
It helps developers structure analytical data and queries for ClickHouse's storage and execution model.

Skill for Claude CodeCodex

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

Good fit Designing MergeTree tables, handling duplicates with ReplacingMergeTree, partitioning data, optimizing queries, and building real-time analytics workflows.

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Install with agentmods
npx agentmods add skills/jsk9999/ai-nexus/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 JSK9999/ai-nexus --skill clickhouse-io
Clone the repo
git clone --depth 1 https://github.com/JSK9999/ai-nexus

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/jsk9999/ai-nexus/clickhouse-io/github.svg)](https://agentmods.dev/skills/jsk9999/ai-nexus/clickhouse-io)
Your own site
<a href="https://agentmods.dev/skills/jsk9999/ai-nexus/clickhouse-io"><img src="https://agentmods.dev/badge/skills/jsk9999/ai-nexus/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/jsk9999/ai-nexus/clickhouse-io"><img src="https://agentmods.dev/badge/skills/jsk9999/ai-nexus/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 11d ago against content hash 8e0d4fd171e1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, 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 11d 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 — 131 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.

config/skills/clickhouse-io/SKILL.md · 430 lines

How it starts

The opening of the file, as written. The whole thing — 430 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 · 430 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. 11d ago First seen · 430 lines · 26 tokens per session scan A 8e0d4fd171e1

Subscribe to this mod's changes

clickhouse-io is a skill published in the GitHub repository JSK9999/ai-nexus (19 stars, last pushed 6mo ago), licensed Apache-2.0. 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 131 lines, and is treated as a copy.

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