agent-clickhouse-io

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

Quality

20%

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Passed

No known issues

Fix and improve this skill with Tessl

tessl review fix ./.agent/skills/agent-clickhouse-io/SKILL.md

Quality

Content

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

This skill is essentially a table of contents with a boilerplate overview. It provides no actionable content in the main file—no code examples, no concrete guidance, no workflow. The overview wastes tokens explaining what ClickHouse is, and the 21 sub-skill links are poorly organized with inconsistent naming conventions and no categorical grouping.

Suggestions

Add a quick-start section with at least one executable ClickHouse query example (e.g., creating a MergeTree table and running an analytical query) to make the main skill actionable.

Remove the overview section explaining what ClickHouse is and its key features—Claude already knows this. Replace with a brief decision guide (e.g., 'Choose MergeTree for general analytics, ReplacingMergeTree for dedup scenarios').

Group the 21 sub-skill links into logical categories (e.g., 'Table Engines', 'Query Patterns', 'Data Ingestion', 'Optimization', 'Analytics Use Cases') with 1-sentence descriptions of when to use each.

Fix inconsistent naming: items 17-21 have numeric prefixes (1-5) that conflict with the main numbering and appear to be best practices that should be in their own section.

Dimension	Reasoning	Score
Conciseness	The overview section explains what ClickHouse is and lists basic features (column-oriented storage, parallel execution, etc.) that Claude already knows. This wastes tokens on concepts that add no actionable value.	1 / 3
Actionability	The skill body contains zero executable code, no concrete commands, and no specific examples. It is entirely a list of links to sub-skills with no actionable guidance in the main file itself.	1 / 3
Workflow Clarity	There is no workflow, no sequencing, and no validation steps. The content is just a flat list of 21 sub-skill links with no guidance on when or how to use them, and no logical grouping or ordering rationale.	1 / 3
Progressive Disclosure	The skill does attempt progressive disclosure by linking to 21 sub-skills, but the organization is poor: links are not grouped by category (table design, query patterns, data ingestion, optimization, analytics), some have inconsistent naming (numbered prefixes on items 17-21 but not others), and no bundle files were provided to verify the references exist. The 'Table Design Patterns' header leads directly into the full list without any structure.	2 / 3
	Total	5 / 12 Passed

Description

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 mentions several relevant topic areas, but it reads more like a category label than an actionable skill description. It lacks specific concrete actions, a 'Use when...' clause, and sufficient trigger terms to reliably distinguish it from other database or analytics skills.

Suggestions

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

List specific concrete actions such as 'Designs MergeTree table schemas, optimizes GROUP BY and JOIN queries, configures materialized views, and troubleshoots INSERT performance.'

Include additional natural trigger terms users might say, such as 'columnar database', 'OLAP', 'MergeTree', 'ReplacingMergeTree', 'ClickHouse SQL', or '.clickhouse' to improve keyword coverage and reduce conflict with generic SQL/analytics skills.

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', 'optimize GROUP BY queries', or 'configure materialized views'.	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' portion is also fairly weak, warranting a 1.	1 / 3
Trigger Term Quality	Includes 'ClickHouse', 'query optimization', 'analytics', and 'data engineering' which are relevant keywords, but misses common user terms like 'columnar database', 'MergeTree', 'OLAP', 'aggregation', 'materialized views', or 'INSERT performance'.	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 skills for other databases like PostgreSQL, BigQuery, or general SQL optimization skills.	2 / 3
	Total	7 / 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: Dokhacgiakhoa/antigravity-ide
Commit: c4a059b

Reviewed: 13 days ago

Table of Contents

Discovery Implementation Validation

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