clickhouse-io

tessl i github:sickn33/antigravity-awesome-skills --skill clickhouse-io

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

58%

Overall

Validation — 63%

Implementation — 65%

Activation — 33%

SKILL.md

Review

Evals

Validation

63%

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
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	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	10 / 16 Passed

Implementation

65%

This skill provides comprehensive, actionable ClickHouse patterns with excellent executable code examples covering table design, queries, and data pipelines. However, it's verbose with unnecessary introductory content, lacks validation checkpoints in workflows, and would benefit from being split into focused sub-documents for better progressive disclosure.

Suggestions

Remove the Overview section entirely - Claude knows what ClickHouse is and its key features

Add validation steps to the ETL and CDC patterns (e.g., row count verification, error handling, retry logic)

Split into separate files: TABLE_ENGINES.md, QUERY_PATTERNS.md, DATA_PIPELINES.md, with SKILL.md as a brief overview linking to each

Add explicit error handling examples for the TypeScript insertion patterns showing what to do when inserts fail

Dimension	Reasoning	Score
Conciseness	The overview section explains what ClickHouse is and lists basic features Claude already knows. The content is generally useful but includes unnecessary explanations like 'ClickHouse is a column-oriented database management system (DBMS) for online analytical processing (OLAP)' and feature lists that add little value.	2 / 3
Actionability	Excellent executable code examples throughout - SQL table definitions, TypeScript insertion patterns, monitoring queries, and analytics queries are all copy-paste ready with realistic field names and proper syntax.	3 / 3
Workflow Clarity	The ETL pattern shows a clear sequence, but most sections present patterns without validation checkpoints. The bulk insert vs individual insert comparison is helpful, but there's no guidance on verifying data was inserted correctly or handling failures in the pipeline patterns.	2 / 3
Progressive Disclosure	Content is well-organized with clear section headers, but it's a monolithic 300+ line file that could benefit from splitting into separate files (e.g., TABLE_DESIGN.md, QUERY_PATTERNS.md, PIPELINES.md). No references to external documentation or supplementary files.	2 / 3
	Total	9 / 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 other database-related 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 terminology variations like 'OLAP', 'columnar database', 'CH', 'analytical warehouse', or 'time-series analytics' 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' are generic enough to potentially overlap with other database or analytics skills.	2 / 3
	Total	7 / 12 Passed

Reviewed

16 days ago

Table of Contents

Validation Implementation Activation

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