clickhouse-io
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
Install with Tessl CLI
npx tessl i github:affaan-m/everything-claude-code --skill clickhouse-ioOverall
score
61%
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillValidation for skill structure
Discovery
33%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 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 |
Implementation
65%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a comprehensive ClickHouse skill with excellent actionable code examples and clear good/bad pattern comparisons. However, it's overly verbose with unnecessary introductory content Claude already knows, lacks validation checkpoints in multi-step workflows, and would benefit from being split into multiple focused files for better progressive disclosure.
Suggestions
Remove the Overview section explaining what ClickHouse is and its key features - Claude already knows this
Add explicit validation steps to ETL and CDC workflows (e.g., 'Verify row counts match', 'Check for insertion errors before proceeding')
Split into separate files: TABLE_DESIGN.md, QUERY_PATTERNS.md, DATA_PIPELINES.md, with SKILL.md as a concise overview linking to each
Add error handling examples to the TypeScript code, especially for bulk inserts and streaming operations
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill includes some unnecessary explanations Claude already knows (e.g., 'ClickHouse is a column-oriented database management system (DBMS) for online analytical processing (OLAP)' and the Key Features list). The content is generally useful but could be tightened by removing basic OLAP/columnar concepts. | 2 / 3 |
Actionability | Excellent executable code examples throughout - SQL queries are complete and copy-paste ready, TypeScript examples are functional, and patterns show both good and bad approaches with clear ✅/❌ markers. All code is concrete and immediately usable. | 3 / 3 |
Workflow Clarity | While individual patterns are clear, multi-step processes like ETL and CDC lack explicit validation checkpoints. The ETL pipeline shows steps but doesn't include error handling or validation between stages. The bulk insert pattern doesn't mention verifying data integrity after insertion. | 2 / 3 |
Progressive Disclosure | The content is a monolithic document (~400 lines) that could benefit from splitting into separate files (e.g., QUERY_PATTERNS.md, TABLE_DESIGN.md, DATA_PIPELINES.md). No references to external files for advanced topics. Well-organized with headers but everything is inline. | 2 / 3 |
Total | 9 / 12 Passed |
Validation
91%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 | |
- Reviewed
Table of Contents
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