sql-master

Database expert - query optimization, schema design

Install with Tessl CLI

npx tessl i github:TurnaboutHero/oh-my-antigravity --skill sql-master

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Overall
score

61%

Review — 49%

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/skill

Learn more

Validation — 10 / 11 Passed

Validation for skill structure

SKILL.md

Review

Evals

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.

This description is too terse and lacks the explicit trigger guidance needed for Claude to reliably select it from a large skill library. While it identifies a clear domain (databases) and two capability areas, it fails to provide the 'when to use' clause and natural trigger terms that would make it effective for skill selection.

Suggestions

Add a 'Use when...' clause with explicit triggers like 'Use when the user asks about slow queries, database performance, SQL optimization, table structure, or designing database schemas'

Expand trigger terms to include natural variations: 'SQL', 'indexes', 'slow queries', 'database performance', 'table design', 'normalization', 'ERD'

List more specific concrete actions such as 'analyze query execution plans, recommend indexes, design normalized schemas, review table relationships'

Dimension	Reasoning	Score
Specificity	Names the domain (database) and two actions (query optimization, schema design), but lacks comprehensive detail about what specific operations are performed within these areas.	2 / 3
Completeness	Describes what (query optimization, schema design) but completely lacks any 'Use when...' clause or explicit trigger guidance for when Claude should select this skill.	1 / 3
Trigger Term Quality	Includes relevant terms like 'database', 'query optimization', and 'schema design', but misses common variations users might say like 'SQL', 'slow queries', 'indexes', 'table design', 'database performance', or 'ERD'.	2 / 3
Distinctiveness Conflict Risk	Database focus provides some distinction, but 'query optimization' could overlap with general SQL skills, and 'schema design' could conflict with data modeling or architecture skills without clearer boundaries.	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 skill provides excellent actionable SQL examples with concrete, executable code covering indexing, schema design, and advanced queries. However, it lacks explicit workflow validation steps for database operations (which can be destructive), includes unnecessary persona framing, and could benefit from better progressive disclosure by splitting advanced topics into separate files.

Suggestions

Remove the persona framing ('You are SQL Master') and closing quote - these waste tokens without adding value

Add explicit validation steps for schema changes and index creation (e.g., 'Verify index usage with EXPLAIN ANALYZE after creation')

Split advanced topics (window functions, CTEs, performance tuning) into separate reference files linked from the main skill

Add a workflow for safe schema migrations with rollback checkpoints

Dimension	Reasoning	Score
Conciseness	The content is mostly efficient with good code examples, but includes some unnecessary elements like the persona framing ('You are SQL Master'), the closing quote, and emoji markers that don't add value. The examples themselves are lean.	2 / 3
Actionability	Provides fully executable SQL code throughout with concrete before/after examples, specific index creation commands, complete schema definitions, and real query patterns. All code is copy-paste ready.	3 / 3
Workflow Clarity	The query optimization section shows a clear sequence (analyze -> identify problem -> add index -> verify), but lacks explicit validation checkpoints. Schema design and performance tuning sections present patterns without clear step-by-step workflows or feedback loops for error recovery.	2 / 3
Progressive Disclosure	Content is organized into logical sections with clear headers, but everything is inline in one file. For a skill of this length (~100 lines of substantial content), advanced topics like window functions, CTEs, and performance tuning could be split into separate reference files with links from the main skill.	2 / 3
	Total	9 / 12 Passed

Validation

91%

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

Reviewed: 7 days ago

Table of Contents

Discovery Implementation Validation

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