database-optimization

Query optimization, indexing strategies, and database performance tuning for PostgreSQL and MySQL

Quality

73%

Does it follow best practices?

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tessl review fix ./skills/database-optimization/SKILL.md

Quality

Content

80%

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

The content is highly actionable and concise, with strong executable examples across PostgreSQL and MySQL. Its main gaps are the absence of an explicit validate-fix-retry feedback loop for database changes and no progressive disclosure splitting of the longer reference material.

Suggestions

Add a validation checkpoint to the optimization checklist: after applying an index or rewrite, re-run EXPLAIN ANALYZE and confirm the plan improved before considering the change done.

Move the longer worked examples (partition DDL, read-replica routing, N+1 detection) into reference files and link them one level deep from SKILL.md to improve progressive disclosure.

Add an explicit "after change" verification note near the Dangerous Patterns section reminding Claude to verify with EXPLAIN ANALYZE and a representative query before declaring success.

Dimension	Reasoning	Score
Conciseness	The body is dense and technical, assuming database knowledge without padding (no explanations of what indexes or B-trees are), and every section earns its place with actionable content rather than the verbose conceptual filler of the score-1 example.	3 / 3
Actionability	Provides copy-paste-ready executable SQL (CREATE INDEX, partition DDL, EXPLAIN ANALYZE), language-specific code, and concrete config values plus a 10-step checklist, matching the fully-executable anchor.	3 / 3
Workflow Clarity	The Query Optimization Checklist gives a clear sequence, but for database operations it lacks an explicit validate-after-change feedback loop (no "re-run EXPLAIN ANALYZE to confirm improvement" step), which the rubric notes should cap this dimension at 2.	2 / 3
Progressive Disclosure	The skill is well-organized with clear headers and no nested references, but at ~170 lines with several substantial examples (partition DDL, N+1 detection) that could live in separate reference files, it fits the score-2 anchor of inline content that could be better split rather than a true one-level progressive disclosure structure.	2 / 3
	Total	10 / 12 Passed

Description

67%

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 specific and clearly niched to PostgreSQL/MySQL performance work, but it omits explicit "use when" trigger guidance, which limits both completeness and trigger-term coverage.

Suggestions

Add an explicit trigger clause, e.g. "Use when optimizing slow database queries, designing indexes, or tuning PostgreSQL/MySQL performance."

Include natural user phrasings in the description such as "slow queries" and "database performance" alongside the technical terms to improve trigger-term quality.

Clarify scope boundaries (e.g. read vs. write optimization, schema vs. query tuning) to further reduce overlap with adjacent skills.

Dimension	Reasoning	Score
Specificity	Names three concrete capability areas ("query optimization", "indexing strategies", "database performance tuning") scoped to two engines (PostgreSQL, MySQL), matching the multiple-specific-actions anchor rather than the partial score-2 example.	3 / 3
Completeness	The "what" is clearly stated but there is no "Use when..." clause or equivalent explicit trigger guidance, which per the judging guidelines caps completeness at 2.	2 / 3
Trigger Term Quality	Relevant terms are present ("query optimization", "indexing", "database performance tuning", "PostgreSQL", "MySQL") but common user phrasings like "slow queries" or "database is slow" are missing, so it falls short of the rich multi-variation coverage expected at score 3.	2 / 3
Distinctiveness Conflict Risk	The dual-engine PostgreSQL/MySQL database-performance niche is clear and distinct, unlikely to conflict with other skills; not generic enough to fall to score 2.	3 / 3
	Total	10 / 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: rohitg00/awesome-claude-code-toolkit
Path: skills/database-optimization/SKILL.md
Commit: ebdf1d5

Reviewed: 2 days ago

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