PluginBench
Skill
Official
Pass
Audit score 90

clickhouse-architecture-advisor

clickhouse/agent-skills

Workload-aware ClickHouse architecture decisioning with provenance-labeled recommendations.

What is clickhouse-architecture-advisor?

This skill guides architectural decisions for ClickHouse systems by identifying workload shape, applying decision frameworks, and attaching official documentation. Use it when designing ingestion patterns, selecting data models, or translating best practices into workload-specific system designs.

  • Identifies workload shape (observability, SIEM, analytics, IoT, financial, mixed OLAP)
  • Applies decision rule files for ingestion strategy, partitioning, joins, and late-arriving events
  • Classifies recommendations as official, derived, or field guidance with explicit provenance
  • Attaches official ClickHouse documentation links to every recommendation
  • Explains tradeoffs and identifies operating bottlenecks in architecture choices
  • Structures responses with workload summary, key decisions, and validation steps

How to install clickhouse-architecture-advisor

npx skills add https://github.com/clickhouse/agent-skills --skill clickhouse-architecture-advisor
Claude Code
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Windsurf
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How to use clickhouse-architecture-advisor

  1. 1.Describe your workload shape, latency targets, data characteristics, and query patterns
  2. 2.The skill identifies the relevant decision rule files (ingestion, partitioning, joins, or upserts)
  3. 3.Review the structured recommendations with provenance labels (official/derived/field)
  4. 4.Check attached official documentation links for deeper context
  5. 5.Validate recommendations using provided SQL, metrics, or smoke tests before implementation

Use cases

Good for
  • Designing real-time ingestion pipelines with appropriate preaggregation and batching strategies
  • Planning time-series retention and partitioning schemes for large-scale observability data
  • Selecting join and enrichment patterns for dimension lookups in analytics workloads
  • Evaluating mutable state handling and late-arriving event strategies for event streams
  • Translating ClickHouse best practices into architecture patterns specific to your data shape and latency targets
Who it's for
  • ClickHouse architects designing new systems
  • Data engineers selecting ingestion and modeling patterns
  • Platform teams building observability or analytics infrastructure
  • Teams migrating workloads to ClickHouse and needing decision frameworks

clickhouse-architecture-advisor FAQ

How does this differ from clickhouse-best-practices?

This skill adds workload-aware decision frameworks and explicit provenance labels. It complements best-practices by helping you choose between patterns based on your specific workload shape, latency targets, and operational constraints.

What does the provenance classification mean?

Official = directly from ClickHouse docs; Derived = logically follows from documented behavior but not stated verbatim; Field = experience-based heuristic that may be situational. Field guidance always includes a disclaimer and relevant official docs.

Can I use this for any ClickHouse workload?

Yes. The skill handles observability, SIEM, product analytics, IoT, financial services, and mixed OLAP workloads. Describe your workload shape and it will apply the appropriate decision rules.

What if I'm uncertain about a recommendation?

The skill explicitly states when confidence is medium or heuristic, and always provides official documentation links so you can verify against the source of truth.

Should I follow all recommendations immediately?

No. Recommendations distinguish between immediate actions and structural redesign. Prioritize based on your operating bottleneck and validate with provided SQL or metrics before production deployment.

Full instructions (SKILL.md)

Source of truth, from clickhouse/agent-skills.


name: clickhouse-architecture-advisor description: 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. license: Apache-2.0 metadata: author: ClickHouse Inc version: "0.1.0"

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.