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cc-skill-clickhouse-io

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

72

1.27x
Quality

59%

Does it follow best practices?

Impact

97%

1.27x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills/skills/cc-skill-clickhouse-io/SKILL.md

The canonical home for this skill is cc-skill-clickhouse-io in sickn33/agentic-awesome-skills

SKILL.md
Quality
Evals
Security

Quality

Content

57%Weight 40%Scale 1-5

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

This is a rich, actionable ClickHouse reference with strong executable examples, but it is a monolithic ~430-line catalog that explains basics Claude knows and, critically, lacks validation checkpoints around its batch and destructive operations. Splitting reference material into bundle files and adding verify-step feedback loops would substantially raise quality.

Suggestions

Add explicit validation/verification checkpoints to batch and destructive workflows (e.g. after bulk insert, run a count/row-count reconciliation; after CREATE TABLE, run EXPLAIN or a test query before loading production data).

Move the exhaustive SQL catalogs and pipeline code into separate reference files under references/ and link to them from a leaner SKILL.md overview, enabling one-level-deep progressive disclosure.

Trim the introductory OLAP/DBMS explanation and the closing 'Remember' summary, and de-duplicate the aggregated-state query that appears in both the AggregatingMergeTree and materialized-view sections.

DimensionReasoningScore

Conciseness

The body is mostly efficient code-with-comments, but it opens with concepts Claude already knows ('ClickHouse is a column-oriented DBMS for OLAP'), repeats the same aggregated-state query in both the AggregatingMergeTree and materialized-view sections, and closes with a redundant 'Remember' summary, fitting the 'mostly efficient but could be tightened' anchor.

3 / 5

Actionability

Provides concrete, mostly copy-paste-ready SQL and TypeScript across table design, queries, inserts, materialized views, and pipelines with GOOD/BAD contrasts, but a few examples are illustrative or partial (e.g. 'INSERT INTO trades VALUES (\'${trade.id}\', ...)' with an ellipsis), placing it just below fully executable.

4 / 5

Workflow Clarity

Content is organized as a topical pattern catalog with well-labeled sections but no sequenced multi-step workflow, and the batch/destructive operations it covers (bulk insert, CDC, ETL, CREATE/DROP) lack any validation or verification checkpoints, so workflow clarity is capped at 3 per the rubric.

3 / 5

Progressive Disclosure

The 430-line body has good section headers but is entirely monolithic with no bundle files (references/scripts/assets absent) and no in-body links, so content that clearly belongs in separate reference files (full SQL catalogs, pipeline code) is inlined — fitting 'some structure, content that should be separate is inline'.

3 / 5

Total

13

/

20

Passed

Description

61%Weight 40%Scale 1-5

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 clearly identifies the ClickHouse niche and surfaces relevant natural trigger terms, but it relies on somewhat abstract capability labels and omits any explicit 'Use when...' trigger guidance, capping completeness. Tightening with concrete actions and an explicit usage clause would lift it.

Suggestions

Add an explicit trigger clause, e.g. 'Use when working with ClickHouse, optimizing analytical queries, or designing data pipelines for high-performance OLAP workloads.'

Replace abstract labels ('patterns', 'best practices') with concrete actions such as 'design MergeTree tables, optimize analytical queries, build materialized views, and batch-load data'.

Include natural synonyms a user might say ('OLAP', 'columnar database', 'real-time analytics') to broaden trigger-term coverage.

DimensionReasoningScore

Specificity

Names the ClickHouse domain plus several areas ('query optimization, analytics, and data engineering best practices'), but these are topic labels and buzzwords ('patterns', 'best practices') rather than concrete verbs like 'extract' or 'merge', so it sits at the domain+1-2-actions level rather than a comprehensive action list.

3 / 5

Completeness

Has a clear 'what' (ClickHouse patterns, query optimization, analytics, data engineering) but no 'Use when...' clause or equivalent trigger guidance, which caps completeness at 3 per the judging guidelines.

3 / 5

Trigger Term Quality

Includes natural terms a ClickHouse user would actually say ('ClickHouse database', 'query optimization', 'analytics', 'data engineering'); a few common variations are missing but keyword coverage is solid, fitting the 'good coverage, a few natural terms missing' anchor.

4 / 5

Distinctiveness Conflict Risk

ClickHouse is a specific named product giving it a clear, mostly-distinct niche with minor overlap risk against general SQL/analytics skills, though the absence of explicit trigger phrases keeps it just below a 5.

4 / 5

Total

14

/

20

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

Table of Contents

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