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clickhouse-architecture-advisor

clickhouse-architecture-advisor

github.com/clickhouseData & databases56210.0k installsUpdated 1w ago
Repository

About clickhouse-architecture-advisor

A skill for making ClickHouse architecture recommendations based on workload shape, decision rules, and official documentation. It is intended for people designing ClickHouse systems and distinguishes documented guidance from derived or experience-based advice.

Key features

  1. 01Workload-specific architecture decisions
  2. 02Rules for ingestion, retention, joins, and late data
  3. 03Official documentation links
  4. 04Labels advice by provenance
  5. 05Calls out uncertainty and heuristics

Use cases

  1. 01Designing real-time ingestion for an identified workload
  2. 02Choosing time-series partitioning and retention patterns
  3. 03Planning enrichment and dimension lookups

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/clickhouse/agent-skills --skill clickhouse-architecture-advisor

After installing, type/clickhouse-architecture-advisorin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

AGENTS.md
metadata.json
README.md
examples/
finserv-market-surveillance.md
observability-high-throughput.md
README.md
siem-security-analytics.md
mappings/
doc_links.yaml
rules/
decision-ingestion-strategy.md
decision-join-enrichment.md
decision-late-arriving-upserts.md
decision-partitioning-timeseries.md
decision-real-time-preaggregation.md
schemas/
recommendation_schema.yaml

Details

From the project README

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

Architecture-specific guidance

Prefer decision frameworks over generic advice. Good responses should:

  • explain tradeoffs
  • identify the likely operating bottleneck
  • separate immediate actions from structural redesign
  • provide target architecture patterns, not just isolated settings

Full reference

See AGENTS.md for the compiled version and examples/ for sample outputs.

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