clickhouse-query-profiling

Profile GKG queries against ClickHouse with the query-profiler CLI. For optimizing query performance, comparing query plans, investigating slow queries, or checking ClickHouse resource usage.

Quality

96%

Does it follow best practices?

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Securityby

Passed

No known issues

Quality

Content

92%

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

The body is highly actionable and concise with clearly sequenced workflows and concrete commands. Its main weakness is progressive disclosure: it is a single large file with reference-style content inline and no one-level-deep bundled references.

Suggestions

Move the detailed output-structure spec and metrics reference into bundled reference files (e.g. references/output-structure.md, references/metrics.md) and link to them from the body.

Consider splitting the diffing/A/B-comparison sections into a separate reference file, keeping only a concise summary in SKILL.md.

Add clearly signaled one-level-deep links (e.g. 'See [OUTPUT.md]') so the overview stays lean while detail remains discoverable.

Dimension	Reasoning	Score
Conciseness	Lean and dense with executable specifics; assumes Claude's competence and avoids explaining concepts Claude already knows, with every section earning its tokens.	3 / 3
Actionability	Provides fully executable, copy-paste-ready mise commands with real flags, JSON query payloads, and concrete diff/output examples.	3 / 3
Workflow Clarity	Multi-step workflows (run-then-analyze, A/B comparison) are explicitly numbered with checkpoints (rebuild between runs, diff results); profiling is read-only so the destructive-operation cap does not apply.	3 / 3
Progressive Disclosure	Well-sectioned but monolithic — no bundled reference files exist and a sizable reference section (output structure, metrics list) is kept inline rather than split out.	2 / 3
	Total	11 / 12 Passed

Description

100%

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 is strong: it names a concrete tool and target, enumerates specific use-case actions, and provides an explicit trigger clause. It uses appropriate third-person voice and avoids fluff.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — profile, optimize, compare plans, investigate slow queries, check resource usage — rather than vague language.	3 / 3
Completeness	Explicitly answers what ('Profile GKG queries against ClickHouse with the query-profiler CLI') and when ('For optimizing query performance, comparing query plans...').	3 / 3
Trigger Term Quality	Uses natural phrases a user would say ('optimizing query performance', 'comparing query plans', 'investigating slow queries') with good coverage, though 'GKG queries' is domain-specific jargon.	3 / 3
Distinctiveness Conflict Risk	The combination of GKG, ClickHouse, and query-profiler CLI defines a clear niche unlikely to trigger for the wrong skill.	3 / 3
	Total	12 / 12 Passed

Validation

100%

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 — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: gitlabhq/orbit-knowledge-graph
Commit: 78fa8a1

Reviewed: about 10 hours ago

Table of Contents

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