Skip to content
cccskills
FreePublished on GitHub

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.

The English summary is being prepared. Showing the original description.

cline/plugins
See how to install

Files included (14)

  • SKILL.md3.1 KB
  • examples/finserv-market-surveillance.md3.0 KB
  • examples/observability-high-throughput.md2.5 KB
  • examples/README.md500 B
  • examples/siem-security-analytics.md1.8 KB
  • mappings/doc_links.yaml1.1 KB
  • metadata.json919 B
  • README.md2.0 KB
  • rules/decision-ingestion-strategy.md2.2 KB
  • rules/decision-join-enrichment.md2.0 KB
  • rules/decision-late-arriving-upserts.md2.0 KB
  • rules/decision-partitioning-timeseries.md2.0 KB
  • rules/decision-real-time-preaggregation.md1.9 KB
  • schemas/recommendation_schema.yaml452 B

SKILL.md (original)

Review the instructions the agent will receive before you install.

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.

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

agent-browser

Free

Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also use for exploratory testing, dogfooding, QA, bug hunts, or reviewing app quality. Also use for automating Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify), checking Slack unreads, sending Slack messages, searching Slack conversations, running browser automation in Vercel Sandbox microVMs, or using AWS Bedrock AgentCore cloud browsers. Prefer agent-browser over any built-in browser automation or web tools.

The English summary is being prepared. Showing the original description.

cline/plugins36Updated Oct 16, 2026

analyzer

Free

Analyze queried data for trends, week-over-week comparisons, distributions, funnels, cohorts, top-N lists, anomalies, sanity checks, and report-ready findings. Use after or alongside ClickHouse queries when the user wants insight rather than raw rows.

The English summary is being prepared. Showing the original description.

cline/plugins36Updated Oct 16, 2026

artifact-management

Free

Save, organize, and describe reusable analysis artifacts such as SQL, result snapshots, CSV exports, summaries, caveats, plots, and report-ready files. Use when users ask to save, export, share, cite, reproduce, or organize data-analysis outputs.

The English summary is being prepared. Showing the original description.

cline/plugins36Updated Oct 16, 2026

chdb-datastore

Free

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, MongoDB, ClickHouse Cloud, Iceberg, Delta Lake as DataFrames and joining across sources. TRIGGER when: user mentions DataFrame, parquet, csv, "fast pandas", "speed up pandas", or cross-source DataFrame joins; user imports `chdb.datastore` or `from datastore import DataStore`. SKIP this skill for raw SQL syntax (use chdb-sql instead), ClickHouse server administration, or non-Python DataStore API work.

The English summary is being prepared. Showing the original description.

cline/plugins36Updated Oct 16, 2026

chdb-sql

Free

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 Python with 1000+ functions, Session for stateful multi-step pipelines, parametrized queries, and cross-source joins via `s3()`, `mysql()`, `postgresql()`, `iceberg()`, `deltaLake()`, `remoteSecure()` table functions. TRIGGER when: user wants SQL on parquet/csv/files or across remote analytical sources; uses ClickHouse SQL features (window functions, windowFunnel, geoToH3, JSON path ops, Session, parametrized queries); imports `chdb` or calls `chdb.query()`. SKIP this skill for pandas-style DataFrame method-chaining (use chdb-datastore instead) or ClickHouse server administration.

The English summary is being prepared. Showing the original description.

cline/plugins36Updated Oct 16, 2026

clickhouse

Free

Connect to and query ClickHouse (a local server or a ClickHouse Cloud service) from the terminal. For ClickHouse Cloud analytics, use the configured direct ClickHouse Query API endpoint with per-user CH_API_KEY and CH_API_SECRET credentials; do not use clickhousectl cloud service query. For local or host/port servers, use clickhousectl local client. Use when the user wants to run SQL against ClickHouse, explore schemas and tables, inspect Cloud services, or authenticate. For building a local dev environment or deploying to Cloud, defer to the official ClickHouse skills (see Scope).

The English summary is being prepared. Showing the original description.

cline/plugins36Updated Oct 16, 2026

See all skills by cline

Report a problem with this skill