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clickhouse architecture advisor

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/skills/clickhouse-architecture-advisor

MUST USE when designing ClickHouse architectures, selecting between ingestion or modeling patterns, or translating best practices into workload-specific system designs. Complements clickhouse-best-practices with decision frameworks and explicit provenance labels.

kindskill
version0.1.0
last tended2026-10-12
written byClickHouse
sourcegithub.com/clickhouse/agent-skills
kept currentwith its source · last read 2026-10-12
in the folderclickhouse skills · 3 of 8 · ‹ chdb sql · clickhouse best practices ›
brought here bykt
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reading2 min

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. 1Identify the workload shape - observability - security / SIEM - product analytics - IoT / telemetry - market data / financial services - mixed OLAP with point-lookups
  2. 2Read the relevant decision rule files in rules/
  3. 3Use mappings/doc_links.yaml to attach official documentation
  4. 4Classify every recommendation as: - official - derived - field
  5. 5Never present field guidance as official guidance
  6. 6If 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. 1rules/decision-ingestion-strategy.md
  2. 2rules/decision-real-time-preaggregation.md
  3. 3Relevant best-practices insert rules

Time-series and retention design

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

Enrichment and dimension lookups

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

Mutable state / late-arriving events

  1. 1rules/decision-late-arriving-upserts.md
  2. 2Relevant 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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