/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.
$ npx -y skills add clickhouse/agent-skills --skill clickhouse-architecture-advisor --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/clickhouse-architecture-advisor
Context preview
The summary Claude sees to decide when to auto-load this skill.
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.
SKILL.md
clickhouse-architecture-advisor.SKILL.mdname: 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.
Read more
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.
The official Agent Skills for ClickHouse. These skills help LLMs and agents to adopt best practices when working with ClickHouse and chdb (in-process ClickHouse for Python). You can use these skills with open-source ClickHouse and managed ClickHouse Cloud.
Repo: clickhouse/agent-skills
Other skills on clickhouse-best-practices.
- /chdb-datastore
Use when the user has tabular data (pandas DataFrame, parquet, csv, Arrow, json) and wants to filter, group, aggregate, join, or speed up slow pandas. Provides chDB DataStore — same pandas API, ClickHouse engine underneath. Also handles reading from S3, MySQL, PostgreSQL,
Open skill - /chdb-sql
Use when the user wants to run SQL — especially analytical SQL — on local files (parquet/csv/json), URLs, S3 paths, or remote databases (Postgres, MySQL, MongoDB, ClickHouse Cloud, Iceberg, Delta Lake) without setting up a server. Provides chDB — embedded ClickHouse SQL in
Open skill - /clickhouse-best-practices
MUST USE when reviewing ClickHouse schemas, queries, or configurations. Contains 31 rules that MUST be checked before providing recommendations. Always read relevant rule files and cite specific rules in responses.
Open skill - /clickhouse-js-node-coding
Write idiomatic application code with the ClickHouse Node.js client (`@clickhouse/client`). Use this skill whenever a user is *building* against the Node.js client — configuring the client, pinging, inserting rows in JSON or raw formats, selecting and parsing results, binding
Open skill - /clickhouse-js-node-rowbinary
Generate TypeScript/JavaScript code that reads/decodes AND writes/encodes ClickHouse RowBinary streams for the ClickHouse HTTP server. Use this skill whenever a user wants to parse or produce `RowBinary`, `RowBinaryWithNames`, or `RowBinaryWithNamesAndTypes`. Node.js only,
Open skill - /clickhouse-js-node-troubleshooting
Troubleshoot and resolve common issues with the ClickHouse Node.js client (@clickhouse/client). Use this skill whenever a user reports errors, unexpected behavior, or configuration questions involving the Node.js client specifically — including socket hang-up errors, Keep-Alive
Open skill

