cc-skill-clickhouse-io

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

Quality

23%

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/cc-skill-clickhouse-io/SKILL.md

Quality

Discovery

32%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description identifies ClickHouse as the target domain and lists broad capability areas, but it reads more like a topic list than an actionable skill description. It lacks a 'Use when...' clause, specific concrete actions, and sufficient trigger terms to reliably distinguish it from general database or analytics skills.

Suggestions

Add an explicit 'Use when...' clause, e.g., 'Use when the user asks about ClickHouse tables, queries, MergeTree engines, or columnar database optimization.'

List specific concrete actions such as 'Designs MergeTree table schemas, writes optimized analytical queries, configures materialized views, and troubleshoots ClickHouse performance issues.'

Include more natural trigger terms users might say, such as 'OLAP', 'columnar', 'MergeTree', 'ReplacingMergeTree', 'materialized views', '.clickhouse', or 'CH queries'.

Dimension	Reasoning	Score
Specificity	Names the domain (ClickHouse database) and some general action areas (query optimization, analytics, data engineering best practices), but doesn't list specific concrete actions like 'write MergeTree table definitions' or 'optimize GROUP BY queries'.	2 / 3
Completeness	Describes what the skill covers at a high level but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill. Per rubric guidelines, a missing 'Use when...' clause caps completeness at 2, and the 'what' is also weak, so this scores a 1.	1 / 3
Trigger Term Quality	Includes 'ClickHouse', 'query optimization', 'analytics', and 'data engineering' which are relevant keywords, but misses common user variations like 'columnar database', 'OLAP', 'MergeTree', 'materialized views', or 'analytical queries'.	2 / 3
Distinctiveness Conflict Risk	'ClickHouse' is a distinct technology that provides some niche specificity, but the broad terms 'analytics', 'data engineering best practices', and 'query optimization' could easily overlap with general SQL, database, or data engineering skills.	2 / 3
	Total	7 / 12 Passed

Implementation

14%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This skill reads as a comprehensive but verbose ClickHouse reference guide rather than a focused, actionable skill. It explains concepts Claude already knows (what ClickHouse is, column-oriented storage), includes an enormous amount of inline content without progressive disclosure, and lacks workflow sequencing or validation checkpoints for multi-step operations like ETL pipelines. The SQL examples are its strongest asset but are buried in an overwhelming amount of material.

Suggestions

Remove the overview section explaining what ClickHouse is and its key features — Claude already knows this. Cut at least 50% of the content by focusing only on non-obvious patterns and project-specific conventions.

Split content into separate reference files (e.g., QUERY_PATTERNS.md, TABLE_DESIGN.md, DATA_PIPELINES.md) and make SKILL.md a concise overview with clear navigation links to each.

Add explicit workflow sequences with validation checkpoints for multi-step operations like ETL pipelines and table migrations (e.g., validate schema -> test with sample data -> run full load -> verify row counts).

Make TypeScript examples fully executable by specifying the exact package name and version (e.g., @clickhouse/client), and replace undefined helper functions with actual implementations or clear interface definitions.

Dimension	Reasoning	Score
Conciseness	The overview section explains what ClickHouse is, lists basic features (column-oriented storage, compression, etc.) that Claude already knows. The document is extremely long (~400 lines) with extensive code examples covering table design, query optimization, data insertion, materialized views, analytics queries, ETL patterns, CDC, and best practices — much of which is general ClickHouse knowledge readily available to Claude. The 'Best Practices' section lists well-known advice. The boilerplate 'When to Use' and 'Limitations' sections add no value.	1 / 3
Actionability	The skill provides many concrete SQL examples and TypeScript code snippets that are mostly executable. However, the TypeScript examples use a vague 'clickhouse' import that doesn't correspond to a well-known package API precisely, the streaming insert example is incomplete/pseudocode-like, and the ETL/CDC patterns reference undefined helper functions (extractFromPostgres, bulkInsertToClickHouse). The SQL examples are generally good and copy-paste ready.	2 / 3
Workflow Clarity	There is no clear multi-step workflow with sequencing or validation checkpoints. The content is organized as a reference catalog of patterns rather than guided workflows. For operations like ETL pipelines, CDC setup, or table migrations, there are no validation steps, error handling guidance, or feedback loops. The ETL pattern is a simplistic code snippet with no error recovery.	1 / 3
Progressive Disclosure	The entire skill is a monolithic wall of text with no references to external files or bundle resources. All content — from basic table design to advanced analytics queries to ETL patterns — is inlined in a single massive document. There's no layering or navigation structure; content that could be split into separate reference files (e.g., query patterns, data pipeline patterns, monitoring queries) is all dumped together.	1 / 3
	Total	5 / 12 Passed

Validation

90%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 10 / 11 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	10 / 11 Passed

Repository: sickn33/antigravity-awesome-skills
Commit: d89c349

Reviewed: about 4 hours ago

Table of Contents

Discovery Implementation Validation

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