clickhouse-architecture-advisor

clickhouse-architecture-advisor is a skill for Claude Code from ClickHouse/agent-skills. It costs 49 tokens per session (680 once invoked), scanned A, original, Apache-2.0.

A decision guide for designing ClickHouse systems, where ClickHouse is a database built for fast analysis of large datasets. It helps match data-ingestion and data-organization choices to the expected workload.

In plain words
What is it for?
Use it when planning ClickHouse for observability, security monitoring, product analytics, device data, financial data, or mixed analytical workloads. It helps choose suitable ingestion and data-modeling patterns.
Why use it?
It makes architecture recommendations traceable to official ClickHouse documentation and separates documented facts from deductions and experience-based advice.

Skill for Claude Code ✓ vendor

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions AGENTS.md.

Part of the clickhouse-best-practices plugin — 11 skills shipped together

Good fit Use it when planning ClickHouse for observability, security monitoring, product analytics, device data, financial data, or mixed analytical workloads. It helps choose suitable ingestion and data-modeling patterns.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/clickhouse/agent-skills/clickhouse-architecture-advisor
About the project

ClickHouse/agent-skills is a collection of packaged instructions that give AI coding agents specialized guidance for ClickHouse databases and chdb, an in-process version of ClickHouse for Python. It helps agents design schemas, write queries, ingest data, analyze results, and troubleshoot performance with ClickHouse or ClickHouse Cloud. The catalogue entries are the repository’s skills, plugins, and instruction for using these systems.

ClickHouse/agent-skills · 532 stars · on GitHub · clickhouse.ai

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 ClickHouse/agent-skills --skill clickhouse-architecture-advisor
Clone the repo
git clone --depth 1 https://github.com/ClickHouse/agent-skills

Made for: Claude Code.

Or install clickhouse-best-practices, the plugin that ships this one along with the rest of its 11 skills.

Its marketplace also offers this one on its own, as the plugin clickhouse-architecture-advisor/plugin install clickhouse-architecture-advisor after adding the marketplace above.

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-architecture-advisor

README.md
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Your own site
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Your own site · 80×15
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Per session 49 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 680 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. Third-party audits
  • Socket pass 19 May 2026
  • Snyk pass 19 May 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found 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 $0.00049 $0.00680
Opus 5 $0.00024 $0.00340
Sonnet 5 $0.00010 $0.00136
Haiku 4.5 $0.00005 $0.00068

Measured 11d ago against content hash edaba60acfe9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

clickhouse-architecture-advisor 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.

skills/clickhouse-architecture-advisor/SKILL.md · 124 lines

How it starts

The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ClickHouse Architecture Advisor

This skill adds workload-aware architecture decisioning on top of clickhouse-best-practices.

Official docs remain the source of truth. This skill must always prefer official ClickHouse documentation when available.

Required behavior

Before producing recommendations:

  1. Identify the workload shape
    • observability
    • security / SIEM
    • product analytics
    • IoT / telemetry
    • market data / financial services
    • mixed OLAP with point-lookups
  2. Read the relevant decision rule files in rules/
  3. Use mappings/doc_links.yaml to attach official documentation
  4. Classify every recommendation as:
    • official
    • derived
    • field
  5. Never present field guidance as official guidance
  6. If a recommendation is uncertain, say so explicitly

Provenance rules

official

Use this when the recommendation is directly backed by official docs.

derived

Use this when the recommendation is not stated verbatim in docs but follows logically from documented ClickHouse behavior.

field

Use this only for experience-based guidance that may be situational. When using field, include:

  • a disclaimer that the advice is heuristic
  • a relevant official doc if one partially applies
  • the reason the advice depends on workload context

Read these rule files by scenario

Real-time ingestion design

  1. rules/decision-ingestion-strategy.md
  2. rules/decision-real-time-preaggregation.md
  3. Relevant best-practices insert rules

Time-series and retention design

  1. rules/decision-partitioning-timeseries.md
  2. Relevant best-practices schema partition rules

Enrichment and dimension lookups

  1. rules/decision-join-enrichment.md
  2. Relevant best-practices query join rules

Mutable state / late-arriving events

  1. rules/decision-late-arriving-upserts.md
  2. Relevant best-practices mutation avoidance rules

Output format

Structure responses like this:

## Workload Summary
- workload:
- latency target:
- data shape:
- primary query patterns:
- operational constraints:

## Key Decisions
- ...
- ...

## Recommendations

### <Recommendation title>

**What**
...

**Why**
...

**How**
...

**Category**
official | derived | field

**Confidence**
high | medium | heuristic

**Source**
- doc link(s)

**Validation**
- concrete SQL, metric, or smoke test

Read the full file on GitHub · 124 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 · 124 lines · 49 tokens per session scan A edaba60acfe9

Subscribe to this mod's changes

clickhouse-architecture-advisor is a skill published in the GitHub repository ClickHouse/agent-skills (532 stars, last pushed today), licensed Apache-2.0. It adds 49 tokens to every session and 680 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.