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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.
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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: Identify the workload shape observability security / SIEM product analytics IoT / telemetry market data / financial services mixed OLAP with point-lookups Read the relevant decision rule files in rules/ Use mappings/doc_links.yaml to attach official documentation Classify every recommendation as: official derived field Never present field guidance as official guidance 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 rules/decision-ingestion-strategy.md rules/decision-real-time-preaggregation.md Relevant best-practices insert rules Time-series and retention design rules/decision-partitioning-timeseries.md Relevant best-practices schema partition rules Enrichment and dimension lookups rules/decision-join-enrichment.md Relevant best-practices query join rules Mutable state / late-arriving events rules/decision-late-arriving-upserts.md 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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| format | Format tag (skill/v1) |
| skill_id | Unique skill ID |
| name | Skill name |
| version | Version |
| description | Description |
| category | Categories (array) |
| trigger_words | Trigger words |
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| exported_at | Exported at (set per download) |
| system_prompt | System prompt body |
| model_config | Model config: provider / model / temperature / max_tokens / top_p |
| examples | Examples |
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