clickhouse-io

tessl i github:ysyecust/everything-claude-code --skill clickhouse-io

ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.

55%

Overall

Validation — 69%

Implementation — 57%

Activation — 33%

SKILL.md

Review

Evals

Validation

69%

Warnings & errors only

Criteria	Description	Result
description_trigger_hint	Description may be missing an explicit 'when to use' trigger hint (e.g., 'Use when...')	Warning
metadata_version	'metadata' field is not a dictionary	Warning
license_field	'license' field is missing	Warning
body_output_format	No obvious output/return/format terms detected; consider specifying expected outputs	Warning
body_steps	No step-by-step structure detected (no ordered list); consider adding a simple workflow	Warning

	Total	11 / 16 Passed

Implementation

57%

This skill provides excellent actionable code examples with good/bad pattern comparisons, making it highly practical for ClickHouse work. However, it suffers from being overly long without progressive disclosure, includes unnecessary introductory content about what ClickHouse is, and lacks validation checkpoints for data pipeline operations that could benefit from explicit verification steps.

Suggestions

Remove the Overview section explaining what ClickHouse is and its key features - Claude already knows this

Split into multiple files: keep quick-start patterns in SKILL.md, move detailed analytics queries to ANALYTICS_QUERIES.md, ETL/CDC patterns to DATA_PIPELINES.md

Add validation steps to the ETL and CDC patterns (e.g., row count verification, data integrity checks before/after operations)

Add explicit error handling and rollback guidance for the data insertion patterns

Dimension	Reasoning	Score
Conciseness	The overview section explains what ClickHouse is and lists basic features Claude already knows. However, the code examples and patterns themselves are reasonably efficient without excessive explanation.	2 / 3
Actionability	Provides fully executable SQL queries and TypeScript code examples that are copy-paste ready. Includes both good and bad patterns with clear ✅/❌ markers, specific table definitions, and complete working examples.	3 / 3
Workflow Clarity	The ETL pattern shows a clear sequence, but lacks validation checkpoints. For database operations that could affect production data, there are no explicit verification steps or rollback guidance. The CDC pattern also lacks error handling.	2 / 3
Progressive Disclosure	This is a monolithic 400+ line document with no references to external files. Content like the full analytics queries, CDC patterns, and ETL examples could be split into separate reference files with a concise overview in the main skill.	1 / 3
	Total	8 / 12 Passed

Activation

33%

The description identifies a clear technology domain (ClickHouse) but lacks explicit trigger guidance and specific concrete actions. It reads more like a topic list than actionable skill selection criteria, and the absence of a 'Use when...' clause significantly limits Claude's ability to know when to select this skill over general database or analytics skills.

Suggestions

Add a 'Use when...' clause with explicit triggers like 'Use when working with ClickHouse databases, columnar storage, OLAP queries, or when the user mentions ClickHouse, MergeTree engines, or analytical data warehousing.'

Replace broad categories with specific concrete actions such as 'Write efficient aggregation queries, configure MergeTree table engines, optimize materialized views, design partition strategies.'

Include common user terms and variations like 'OLAP', 'columnar database', 'CH', 'analytical warehouse', '.clickhouse' to improve trigger term coverage.

Dimension	Reasoning	Score
Specificity	Names the domain (ClickHouse database) and mentions some actions like 'query optimization, analytics, and data engineering best practices' but these are broad categories rather than concrete specific actions like 'write aggregation queries' or 'configure table engines'.	2 / 3
Completeness	Describes what the skill covers (ClickHouse patterns and optimization) but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill.	1 / 3
Trigger Term Quality	Includes 'ClickHouse', 'query optimization', 'analytics', and 'data engineering' which are relevant keywords, but misses common variations users might say like 'OLAP', 'columnar database', 'MergeTree', 'analytical queries', or 'CH'.	2 / 3
Distinctiveness Conflict Risk	'ClickHouse' is a specific technology which helps distinctiveness, but 'query optimization', 'analytics', and 'data engineering best practices' could overlap with general SQL skills or other database-specific skills.	2 / 3
	Total	7 / 12 Passed

Reviewed

2 days ago

Table of Contents

Validation Implementation Activation

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